Blogs

Problem #1: Inefficiency due to human factors.

Problem arises when the Company doesn’t receive yield as per the efforts and investment made by them. Due to various human factors throughout the chain the estimated yield is not received by the company.

Solution: By providing satellite data to monitor farms at different levels.

Farmonaut has provided satellite data to reduce the human errors at different levels such as clusters, region and farmer level. The various satellite parameters help to track consistent actions taken on the field which examines the inefficiencies.

Problem #2: Burdensome Machinery Management at large scale.

The management issues caused are also due to human malfunction. Company’s Unawareness regarding the usage of machinery creates chaos which leads to loss in the capital invested by the company.

Solution: By Tracking each and every machinery through GPS for various data.

GPS trackers help to capture data every 10 secs and pass on to the systems. Hence, the data captured can be used for multiple benefits such as performance evaluation, to know oil usage, work done, capacity of machinery, etc.

PROBLEMS & SOLUTIONS

Farmonaut has been providing solutions to farmers and businesses at large scale to solve different problems faced in the agriculture sector.

We have managed to monitor over 10 million hectares of land world-wide and mapped over 1 lakh farms globally benefiting more than 50,000 farmers.

We are also working with 25+ large scale businesses including Coromandel International, Torforte Innovation based in Australia, Zr3i.com in Egypt, ITC, Godrej Agrovet, Mulpuri Group and many more.

ABOUT US

Satellite data captured are being processed and segregated by the Farmonaut system which makes them easy to understand. Monitoring large numbers of farms can be inaccurate and tedious. The Farmonaut system captures the data and generates reports according to the clusters. The dashboard, data and reports can be obtained in Uzbek language which makes it more convenient for the locals.

WHY FARMONAUT..???

SATELLITE BASED CROP HEALTH MONITORING:

It is a technique which helps companies to manage and organize their vehicles. In order to manage machinery Farmonaut provides a system which monitors and tracks each and every machinery.

How does it work?

GPS devices are installed on each and every machinery of TTG. The devices are connected to Farmonaut’s servers. The data is captured by devices and it is received on the server every 10 seconds. There are many different parameters that are captured by the devices such as Coordinates (Latitude Longitude), Speed, Angle, Stopped or Working, oil container is open or not, etc.

  • FLEET MANAGEMENT
  • Field mapping
  • Mapping of farms at large scale can be done with ease and accurately.
  • Soil carbon content
  • Soil carbon content tracking for better yield and knowing status of necessary actions taken in the soil.
  • Satellite based soil health monitoring
  • Timely data on diseases and pests would help n tracking whether the required inputs have been given or not.
  • Crop area estimation
  • It can be helpful to know the areas under which crop is sown and make decisions on contract farming regarding capital and machinery.
  • Identifying location requiring irrigation
  • Helps to know the location where irrigation is required and track the actions taken by farmers.
FEATURES  USE
Interface to plan jobs for machine based on needs Can get an expertised driver for a particular region.

Helps in job management effectively

Choose accessories for a particular machine. Can pick equipment as per pocket allowance and based on requirement.
Interface for performance tracking based on machine type. Helps in inventory management, market predictions and knowing future requirements.
Dashboard in Uzbek Language anyone can easily understand.
Assigning team member for each machine Can evaluate performance in different work domains.
Estimation of machine capacity. Helps in overall performance and requirements for long run viability.
Generated cumulative data Helps in estimation of optimal machine performance.
Day-to-day data entry datasets Know underperforming machines

Helps in comparison of planned and actual work

Booking machines by our farmers by Android Easy to book.
Introducing payment plans or accounts Helps in account management of organization
See performance of clusters and individual machines. Helps in evaluating performance at macro level for resource allocation and tackle unforeseen situations.
Fuel consumption monitoring Stops any false reporting or incorrect strategies used by humans.

Advanced features provided as well as proposed by Farmonaut for Fleet management:

The motion tracking feature and the parameters tracked helps to create insights/visualization of the machinery used on the dashboard as follows:

  • Track real-time location of farm machine updated every 10 seconds.
  • Track total distance covered by machine on a given day.
  • Track total number of hours machine was running.
  • Track current speed, maximum speed and average speed of machine.
  • Track number of farms visited on a particular day.
  • Track the amount of time spent by machine on each farm.
  • Track entry time and exit time of the farm machine on each farm it visited.
  • Track area of each individual farm.
  • Time lapse feature backtracks the path machine travelled through.
  • Maintain an accounting record of each field at which machine went.
  • Access to the historical data of the machine.
  • GPS devices work on any power operated machines.
  • Home location fencing.
Maintenance records of all vehicles and accessories with its expenses. Helps to know market trends and identify problem areas.
Monitor driver attendance and work performance Helps in effective management of payroll and manage schedules.

SERVICES CARRIED OUT FOR TTG

For the month of July and August in 2022 for cotton farming, Farmonaut has mapped and monitored 8800 farms contributing to over 2 lakh+ hectares of land. The reports for which were generated through satellite visits every 5 days. Around 12 reports were generated throughout the period of 2 months which were in English and Uzbek language.

Farmonaut has also created a custom account for TTG on the Farmonaut’s platform for access of the data throughout the period.

Farmonaut has also created a customized page to access the report in infographics format as shown below.

Dashboard in English Language

Dashboard

The dashboard is provided in the Uzbek and English language. It contains various satellite images for crop health, irrigation, soil carbon, etc. the reports for clusters and individual farms can be accessed through the dashboard.

Dashboard in Uzbek Language

Excel Reports

The Excel reports are generated by the system automatically. The parameters obtained in reports are:

  • Total Area covered
  • Total Good area
  • Total Bad Area
  • Irrigation required
  • Fertilizer required

The report generated is colour coded in red for the data which requires irrigation, fertilizer or are in bad condition.

Farm reports can be downloaded in Uzbek language for easy understanding. The report contains all the satellite images and weather data obtained from weather stations.

Individual Farm Report

2nd sheet of Excel Report

2nd sheet:  the clusters are segregated into regions. It also contains information on region leaders and contact.

1st sheet of Excel Report

The excel report contains 3 sheets which includes all above mentioned parameters:

1st sheet: shows data of individual clusters collectively.

 

3rd sheet of excel report showing individual farmers

3rd Sheet: Each individual farm is mentioned under the particular regions. It contains all the information of individual farmers and region leaders such as contact Number. To know the area of an individual farm, the 1st column of the sheet has a Link to Farm stating “See Farm on Map”. It directs the user to the Farmonaut map showing the satellite image on map.

2nd sheet showing Regions expanded

 

Fleet Management for TTG

Farmonaut has configured a TTG machine for a period of 2 months (July – August 2022). The device installed tracked the machine on daily basis. The testing carried out is still observation and Farmonaut servers still received data on daily basis. The below images show machine tracked. Also, Farmonaut has incorporated the advanced feature as proposed. Hence, we are ready to carry on the work.

Importance / Benefits to TTG

  • Can cross verify with farmers for authenticity of action taken on farms for improvement of yield.
  • Know areas where irrigation/fertilizers are required.
  • Track the chain for knowing at what stage error has occurred.
  • Helps in making decisions whether to grant investment to individual farmers.
  • Decreases the inefficiency caused by human factors.
  • Reports are concise and centralized for trouble-free at macro-level.
  • Can access data from cluster level to Farm level.

 

  • INVESTMENT + EFFORTS + TECHNOLOGY = INCREASES YIELD OUTCOME

WHY USE FARMONAUT?

 

 

With Traditional/Manual method With Farmonaut
No. of farms 8800 farms 8800 farms
Average time required to survey per farm 15 minutes (0.25 man hours) 1 minute (0.017 hours)
Visits per farm per month 6 visits 6 visits
Hours required to survey 8800 farms = 8800*0.25*6

–> 13,200 man hours/ month

= 8800*0.017*6

–> 900 hours/ month

Farmonaut decreases 94% of your survey time compared to traditional/manual survey method

Crop classification helps to know which crops are grown in which areas. The estimation of agricultural production is necessary for decisions to be made. The crop area estimation allows the farmers to predict or calculate the tonnage of the particular crop. Identifying the specific crop grown at different village level, taluka level, district level and state level can be done. The estimation and identification of the crops could be useful in many ways:

  • Deciding agricultural policies.
  • Planning supply chain management.
  • Making decisions on procurement, storage and distribution.
  • Adjusting effective food prices.
  • Allocation of resources.
  • Identify the purpose of the vegetation such as food, feed and fiber.
  • Can help in controlling water usage.

How does it work?

In order to identify a particular crop or vegetation the model requires few sample images to train the model for classification. How the classification model works can be explained as follows with an example.

# Training data and classes are needed: For example, if an area is sown with paddy the model must know the crop that has to be classified. The class must be paddy in this case.

# Sample data: In order to train the model few sample locations are needed. The sample location helps the satellite to create wavelength and identify the crop. Hence helps to know the crop cycle and the changes taking place during every satellite visit. Marking locations is known as Ground Truthing.

# Study images of location: In order to predict, the unknown study area location must be added which identifies whether the class mentioned is expected in which area. For example, which locations are expected to have rice and which areas do not expect rice.

Problematic area

The working of the crop area estimation manually creates many problem in the process such as

  • Requires more time.
  • Resources are required in a high amount such as labor.
  • Cost increases.
  • Accuracy gets compromised.

What does Farmonaut provide?

Farmonaut is providing Crop Area Estimation to deal with the problem caused due to the manual estimation. It helps to predict accurately and precisely the crop classification.

How to access data?

Once you login to your Farmonaut account. On the Farmonaut platform the Crop Area Estimation panel is added by which you can access it. By clicking on the “Crop Area Estimation”, DashBoard opens. Dashboard contains all the paid and unpaid area Estimations which are added by you as shown in the image.

  • To add new crop:

The Dashboard has a button on the top right corner, “Add New Crop”. Click on it. A dialog box opens where you have to enter information as

  • Crop Name: Select crop you want the data for.
  • Study Year: Select year for which you want to have classification for. Can be done for past years.
  • Sowing Date: The date the crop was sown as it can be different in different states and countries.
  • Harvest Date: The Expected harvest date of the crop.
  • Total Area: the area in which the crop is sown.
  • Country: The country in which the farm is located.
  • Contact Number: Your contact number for future useful deeds.

After the information is entered. Click on “Submit”.

A dialog box will appear for the Payment stating the amount to be paid. Click on the “Pay” button to complete the payment.

In case of large areas, it suggests a request and hence the Farmonaut team will contact you. Also email and contact number are provided in case you want to contact our team. And then click on the “Submit Requirement” button.

  • Ground Truthing

In order to classify the crop, the system needs few locations on which the crop is shown, known as ground truthing. It can be done through web or mobile applications.

How to do Ground truthing?

Step 1: Login with the ground truthing email and ground truthing password provided on the dashboard for a particular crop request on Farmonaut platform.

Step 2: Select atleast 20 locations on the field to train the model.

  • Study Location:

Locations for which you want the classification are to be given. For which following steps are to be followed:

Step 1: Login on the Farmonaut platform using Study Email and Study Password provided on the Dashboard.

Step 2: Select the study area by adding a new field.

Step 3: Submit location for which you want classification done.

On submitting all the information, the Farmonaut system will study the information and process it for the crop classification. The results will be then sent to the farmers on Email. Also, you can check the data on the study email account.

DEM (Digital Elevation Model)

All fields/farms are not of the same elevation, with different fields lying on different slopes it requires to know the slope. DEM helps in representation of elevation data to depict the terrains. It represents the bare ground of the earth by eliminating the trees, buildings and any such other objects. Hence, the elevation would be accurate according to the needs of the user by using DEM.

Problems

Due to excessive rainfall or intensive irrigation in various areas, the water logging in the terrain leads to the damage of crops. Elevation in the farms clogs the water at the low terrain areas and hence creates issues such as soil erosion, soil degradation, etc.

To get an idea of the terrain regions of the farmland Farmonaut has been providing DEM satellite data for avoiding such issues caused by elevation.

Solution provided by Farmonaut

Farmonaut technologies is providing satellite data to all the farmers for knowing their farm crops better and helping them handle it. DEM data are also provided by farmonaut which are easy to analyze and interpret for your farms. The farmers can have a look at the DEM image of their farm in different color codes which is analyzed using the analysis scale which represents the low terrain and high terrain region.

Knowing the terrain at different areas on the farm, the farmer can take precautions for the water logging conditions that may occur such as building temporary water drain passage or any other water removal mechanism.

How to Access the DEM image?

Step 1: Login to your account on the Farmonaut application.

Step 2: Select the farm you want the satellite image for.

Step 3: Click on the DEM button under the image for topography.

Step 4: the DEM image will be displayed on the farm you selected.

Step 5: Interpret the image using the analysis scale provided below the farm. Shown in figure below.

Satellite data obtained for the vegetation are based on what actually has been seen. For example, for the land which is sown, the soil is exposed to the satellite and based on which the satellite images are generated. Similarly the height of the vegetation also plays an important role in knowing the crop health and condition. Interpretation of such data requires different color coding or analysis. The accuracy of crop health will help farmers in managing their farms better.

Problem:

Vegetation at an early stage seems like the soil is more exposed to the satellite and hence the indices obtained would be based on the default analysis scale. However for taller vegetation the data images obtained are much more accurate.

The issues faced at an early stage of vegetation would not be recognised and hence the decision to be made would be unidentified. To clear such circumstances Farmonaut has introduced 2 types of colormap.

Colormap

Colormaps helps to recognised the condition of vegetation at early stages.The two kinds of colomaps are:

  1. Colormap 1: It ranges from 0.1 to 1. It can also be called as the default color map which is shown at first for all indices. Its color ranges from green to red stating green as good vegetation and red as danger. The color map is as shown in the figure below.

  1. Colormap 2: It ranges from -1 to 1. It is basically used for the early growth stages or for low heighted vegetation. The color ranges from different shades of green. It is recommended to use colormap 2 during the early growth stages. The colormap 2 is shown in the figure below.

The colormap 2 states the accuracy and sensitivity of the crops. The color map 1 range 0.1 to 0.2 is magnified and shown as the colormap 2 in different shades of green. When a whole farmland is sown on a particular day still there may be growth issues in some areas which cannot be identified with the colormap 1 and hence colormap 2 can be used. However, the colormaps are available for NDVI, NDRE, NDMI, NDWI, SAVI, EVI, VARI and RVI. The colormaps are not required for the TCI, ETCI, Hybrid image, DEM and Colorblind Visualization.

How to Access Color maps?

Step 1: Login to your account on the Farmonaut application.

Step 2: Select the field you have sown recently or it at an early growth stage.

Step 3: Select the image you want such as NDVI.

Step 4: Click on the colormap 1 or 2 as per the vegetation.

Step 5: Analyze the image shown as per the scale.

Radar Vegetation Index (RVI)

Radar data is obtained by a detection system with the use of radio waves which helps in determination of some parameters such as altitude, height, etc. Radar vegetation Index is used in agriculture for knowing the condition of the vegetation by measuring the linear scattering intensities. The radar data are obtained by the usage of Synthetic Aperture Radar. RVI can also be known as the alternative to NDVI (Normalized Difference Vegetation Index).

Problem caused:

Different satellite data has been collected for knowing crop health, soil health and irrigation. Obtaining data through satellite can cause issues during cloud cover. Cloud cover specially occurring in monsoon season makes it infeasible to collect data of crop health during the satellite visit.

“To deal with the cloud cover and to solve the issues faced in collecting data through satellite during cloudy weather, Farmonaut provides Radar Vegetation index in time series analysis.”

Farmonaut offers:

The satellite data is captured when the satellite passes through the field. The satellite visit occurs every 5 days to capture the crop health data. Monsoon season generally faces cloud cover everyday which makes it difficult for the satellite to capture the data during every visit. Not only during monsoon but also during regular days cloud cover can be seen on the field. The satellite visibility gets blocked and hence results in no data.

Not compromising on the data and to overcome the inconvenience caused by cloud cover to capture the data, Farmonaut has introduced RVI which helps get crop health data during the cloud cover. The data obtained can be visualized in the time series by selecting the date on which farmers need the data. The Radar data recorded assure that during any condition the crop health data would be provided to the farmers.

How to Access RVI Data?

Step 1: Login to your account on the Farmonaut application.

Step 2: Select the farm you want the data for.

Step 3: When there is cloudy weather, Go to Radar Vegetation Index in the Controls.

Step 4: Select the date for which you want to visualize the data.

Step 5: The crop health image appears, analyze it using the scale provided.

There are less number of people having color blindness who deal with identification of colors on a daily basis. There are multiple kinds of color blindness like Red-Green Colorblindness, Blue-Yellow Colorblindness, Complete color blindness, etc. Where they have issues in differentiating colors such as red and green or in some cases even all the colors. Even some farmers do have color blindness. For which they cannot be neglected for the services we provide.

Problem faced:

Colourblind people face challenges in identifying multiple colors. Due to various kinds of colorblindness one may or may not be able to differentiate between different colors. However, Color coded images are easy to interpret and understand, they’re not of much use to colorblind farmers.

Farmers having color blindness would face difficulty in interpretation of coloured satellite images. To provide a solution to this problem, Farmonaut has developed the Colourblind Visualization feature.

Colorblind Visualization

Farmonaut has taken into account the colorblind farmers as well and developed colorblind visualization. The satellite image for a coloublind farmer would be in black and white color contrast because all types of colorblind people can at least differentiate black and white colors. The analysis of which would be much easier for them. Hence, the color coded images of crop health and irrigation are converted to black and white images without compromising on the depth and quality of images. This feature is available on Android apps as well as on the Web.

Receive and Analyze the Colorblind Visualization

Step 1: Login to your account on Farmonaut Application.

Step 2: Select the field you want to see data for. As a default it will show a color coded image.

Step 3: Click on the Colorblind Visualization button, it will display the black and white coded image.

Step 4: Interpret the image using the analysis scale provided. Note: Cloud cover areas would be displayed in black as well so that farmers can look after those areas too.

The analysis scale is represented as follows:

  • Black: the area requires a visit to the farm to check the crop health or irrigation issues.
  • White: area has the irrigation issues only
  • No color: the area is in good condition

Remote Sensing data are of different types for different use cases in agriculture. Farmonaut is providing around 18 different satellite data parameters for examining your farms. The data must be understood first to take necessary or required actions. Satellite data for different problems are:

  • For crop health monitoring: NDVI, EVI, SAVI, NDRE, VARI
  • For irrigation: NDWI, NDMI, Evapotranspiration, DEM
  • For Cloud Cover: RVI
  • For Soil health: SOC

Problem:

Majority of individual farmers in India have less knowledge on using smartphones. However, there are few farmers which own smartphones but aren’t aware of the features or operations that can be performed. Due to the lack of educated farmers it can be difficult for them to understand all the different satellite data provided by us. Imposing the use of multiple satellite images can overwhelm the early adopter of the technology.

To tackle the problem faced, Farmonaut has come up with images known as “Hybrid image/analysis.”

What is a Hybrid Image?

“Hybrid image includes all the parameters of crop health, irrigation, soil and cloud cover in a single image for easy understanding of new farmers.” Not compromising on the quality of data, the Farmonaut system processes the data into a hybrid image, making it readable and accessible. One image makes it easier for beginners to get used to the technology and understand it as well.

Need of Hybrid Image

  • New farmer friendly: Analyzing multiple images for a new user/ farmer can overburden the farmer to process the needed information. Hence,
  • Easy to interpret: Undereducated farmers can easily access and interpret the hybrid images rather than multiple images. The color coding analysis scale available gives a simplified explanation of the image.
  • Always Handy: Hybrid images can be seen on the web, smartphone app and also can be shared.

Access and Understand Hybrid Image

Step 1: Farmers must login to the application to access the data.

Step 2: After logging, the fields already marked are seen in the My fields icon. Click on “My Fields”.

Step 3: A page showing the map opens. Select the field you want to get an image of.

Step 4: The field visible will be shown with a hybrid image. The Hybrid image of the field is shown by default.

Step 5: The analysis scale is provided at bottom of the page as shown in figure. The analysis can be obtained in any desired language for local farmers to understand. Different colors indicate different issues caused.

Once you get along with the Hybrid images, we encourage you to use all the images and parameters provided by us for better health of your crops.

Tutorial of web app:

Farmonaut Hybrid Image And How To Interpret It

Knowing the condition of your crop irrigation is crucial to avoid degradation in crop health. Through remote sensing knowing the water content and moisture content is possible. The data can indicate the area which has low, high or medium water content, moisture content and evapotranspiration rate.

Different parameters provided by Farmonaut
Due to the above mentioned importance of irritation data, farmers should be aware of it for better production. Hence, Farmonaut has provided this data to farmers to know the condition of their crops and take necessary irrigation practices to avoid the drying of crops. Farmonaut provides the irrigation parameter data on the web app as well as mobile app.

The different irrigation parameters provided by Farmonaut are as follows:

NDWI (Normalized Difference Water Index)

NDWI is an index which states the plant water content that can help us control irrigation, significantly improving agriculture, especially in areas where meeting the need for water is difficult. The high NDWI values correspond to high plant water content and coating of high plant fraction, whereas the low NDWI values correspond to low vegetation content and cover with low vegetation. NDWI rate will decrease during periods of water stress.

NDMI (Normalized Difference Moisture Index)

NDMI states the moisture content in the soil which helps in monitoring the drought condition of the areas. The kind of vegetation must be taken into account to further know the amount of water to use at particular growth stages of crops.

Evapotranspiration

Evapotranspiration is the loss of water from the soil surface as well as from the plants. It measures the rate at which evaporation and transpiration occurs at multiple locations on the farm. Through evapotranspiration one can easily schedule the irrigation based on the indicators received by the data. Nevertheless, it can be ignored if NDWI and NDMI data result in a good condition.

How to access data?

Step 1: Login to your account on the Farmonaut application.

Step 2: Select the field You want to get data for.

Step 3: In the Mobile application, Go to the settings -→ In the controls tab select the NDWI / NDMI / Evapotranspiration -→ Click Show on Field

In Web application, click on NDWI / NDMI / Evapotranspiration button provided on the left side. The satellite images will be shown on map.

Step 4: Interpret the data by the analysis scale provided and take action as per the following outcomes.

Interpretation of data using all parameters:

Parameters Condition Action to be taken
NDWI

NDMI

Evapotranspiration

High

High

Low

No irrigation would be required.

The corp condition would be good until the next satellite visit.

NDWI

NDMI

Evapotranspiration

High

High

High

Requires frequent irrigation

Due to high evapotranspiration rate, the water reduces over time hence requires irrigation frequently

NDWI

NDMI

Evapotranspiration

Low

Low

Low / High

Irrigation is highly needed

Water content in plants and soil is reduced hence irrigation must be done irrespective of Evapotranspiration.

NDWI

NDMI

Evapotranspiration

Low

High

High / Low

Examine the issue on the field.

It indicates that plants aren’t receiving water hence the water uptake in plants is low.

NDWI

NDMI

Evapotranspiration

High

Low

High / Low

Water content in soil must be maintained

Not enough water content in soil can result in drying of plants or can cause some other issues until the next satellite visit.

Farmonaut has been working with the large corporations by providing them the system for the use of better management of the farms. They have been using the “Remote Sending technology” to grab the data at large scale for the farmers to impart better management of farms. Managing multiple farms at a large scale can be tedious and inaccurate at some point. Hence, to overcome the drawbacks faced by the corporates, Farmonaut is providing Admin application for the large corporates. Through the mobile application they can map fields and monitor, manage and access data with the help of advanced web-app.

Benefits to Large Corporations:

  • It helps to manage farms at a large scale at district/village level.
  • Data can be obtained in a couple of seconds within no time.
  • Track the crop health and progress at every stage.
  • Can provide data to multiple farmers at a faster rate.
  • Help farmers to increase the yield and productivity.
  • Downloading, sharing and accessing data is more convenient.

About Data you will get:

Using the satellite data provided by Farmonaut in the form of comprehensible information, farmers can:

  • Reduce chemical/Fertilizer consumption by applying it only at the locations where crop health is in bad condition.
  • Reduce Labour costs by directing the labour only to the areas where crop health is low.
  • Reduce irrigation water wastage by knowing the water stress.
  • Increase the overall yield.
  • Maintain nutrient composition by knowing the soil carbon content.

Some of the concepts most commonly used for high level analysis by Farmonaut are NDVI, NDRE, EVI, VARI, SOC, NDWI, etc according to the use cases of each parameter.

  • For Crop health of crop at early growth stage

NDVI (Normalized Difference Vegetation Index)

NDVI is used as a measure to identify the state of plant health based on the light reflected by the plant at certain frequencies. Though we cannot perceive it with our eyes, everything around us (including plants) reflects wavelengths of light in the visible and non-visible spectrum. Taking into account how much of a certain wavelength is reflected, we can access the current status of plants.

EVI (Enhanced Vegetation Index)

EVI is further an optimized index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a decoupling of the canopy background signal and a reduction in atmosphere influences.

  • For Crop health of crop at later growth stage

NDRE (Normalized Difference Red Edge)

NDRE is a spectral index that helps in gathering the data at the later stages of a crop when chlorophyll content is relatively higher in the crop.

  • For irrigation:

NDWI (Normalized Difference Water Index)

NDWI index can help us control irrigation, significantly improving agriculture, especially in areas where meeting the need for water is difficult. The high NDWI corresponds to high plant water content and coating of high plant fraction, whereas the low NDWI values correspond to low vegetation content and cover with low vegetation. NDWI rate will decrease during periods of water stress.

Hence, through NDWI, the early detection of water stress can prevent many of the negative impacts on crops.

NDMI (Normalized Difference Moisture Index)

NDMI is used to know the moisture index/water stress in vegetation which helps in monitoring the drought condition of the areas. The kind of vegetation must be taken into account to further know the amount of water to use at particular growth stages of crops.

Evapotranspiration

Evapotranspiration measures the rate at which evaporation and transpiration occurs at multiple locations. Through evapotranspiration one can easily schedule the irrigation based on the indicators received by the data. Nevertheless, it can be ignored if NDWI and NDMI data result in a good condition.

  • For Advance Analysis

VARI (Visible Atmospherically Resistant Index)

VARI is minimally resistant to atmospheric effect, allowing vegetation to be estimated in a wide variety of environments. Hence, it is ideally recommended to be used for arm level decision making if TCI or ETCI images show visible atmospheric distortion such as mild clouds or haze above the field.

  • For Topography

DEM (Digital Elevation Model)

DEM is used to know the waterlogging prone areas in the field. During heavy rainfall or excess irrigation, the areas where the water logged or flood occurs can be identified through DEM. Hence, by knowing such areas the passage for the outsourcing of the water can be ensured by installing more motors in the area.

  • For Soil Health:

Soil Carbon Content (SOC)

SOC is a measurable component of the soil organic matter that indicates the better health and yield of any land once the cultivation process ends. Remote Sensing technology plays a vital role In enabling farmers to ensure high SOC content by taking the right measures at the right time and the right place. Farmonaut creates a SOC image with a colour map of the percentage of organic matter present in the selected field. The land area appears green in the colour map if SOC content is more than 5% and red if the SOC content is less than 1%. Once the locations with lesser SOC levels are identified by Farmonaut, farmers can get the soil testing done on specific regions, and the required actions can be taken.

  • For Crop Health during Cloudy Weather

RVI (Radar Vegetation Index)

RVI is measured by the backscattering which does not affect the data. The RVI data was designed to be the time series data which can be a great alternative to the NDVI. However, RVI can be obtained at extreme weather conditions when the satellite data could not be obtained due to cloudy or any other weather conditions. Hence, Farmonaut ensures the data at any conditions.

  • Farmonaut also provides RGB images of the field. (Coloured satellite images)

TCI (True Color Image): It is basically raw image of the field captured by satellite of a particular farm. This is not an index image, but a RGB representation of how the field looked like in human perceivable colors upon its last visit.

ETCI (Enhanced True Color Image): It is a TCI image processed by our own systems to enhance the land features which were not so explicitly visible in the raw TCI image.

Farmonaut Admin Application:

The admin application of Farmonaut is available on mobile as well as on Web for easy use for corporates. To make it more applicable the applications are interconnected which allows to see the changes made on any platform. The data/reports provided is also available in 50+ languages making it convenient for more farmers. The application is beneficial to the chain of people using it and providing it.

  • Farmers: They receive data on the crop health and weather data from the ground team on Any social media such as WhatsApp, SMS, Email as per the preference of the ground team.
  • Ground Team: They use the mobile application to stay in connection with the farmers and provide them the data. They also use it to mark/geotag the farms.
  • Office Team: They can see the farms marked and provide the necessary advisory to the farmers.

Mobile Application:

How to login to the application?

The access to the application must be provided by your organization in order to login. As you open the application it has an option to Add Farm. Once you click on “Add Farm”, username and password must be used to login which are provided by the organization.

How does it segregate the data?

Large corporations such as Coromandel, Godrej Agrovet are required to geotag the farms at multiple locations. In order to geotag multiple locations, segregation of the farms based on village area such as Number of farms geotagged from village 1 and village 2 would be helpful for providing services effectively and faster.

Farmonaut application has been designed in such a way that it smartly based on your current location can segregate the farms and provides the administrative boundaries of that particular village. It also gives a list of nearby villages, by which geotagging in those villages can be done. Once the user clicks on the village, the platform also shows the already geotagged farms in that village boundaries.

How to geotag the farms?

To geotag new farm on the map, it can be in any of the to ways:

  1. By walking along the field boundary and adding the current location as the boundary point.
  2. By pressing on the screen on the boundary point of the field. The field gets added.

Once the boundary points are selected on the map, the user can add the data such as Name of farmer, Phone Number and Primary Crop of the farm. After which the field can be submitted by clicking on “Submit Field”.

How to know information about already geotagged farms?

Once the boundary of the village is visible, the geotagged farms are also visible in that particular village. To know information about it, the user can select the farm and the information can be seen from the dropdown menu provided above the map. The information contains Name of Farmer, Phone No., Crop and Area in sq.m, sq. feet and acre. The information can also be visualized by clicking on the farm boundary which directs the user to a screen which contains all the information and also some major Edit options that could be useful.

Various Edit Features Available:

All of the edit features are available on mobile as well as web application. When the user clicks on the boundary of an already geotagged field, it directs to the screen which contains information about the farmer and his/her field. This window also has the following options from editing boundaries to adding farmer’s information.

  • Add Farm Input Data: It allows the user to add the data on farm inputs throughout the entire crop season based on the actions taken. It includes data points such as What farm input has been given by the farmers? What type of input was it (seed or Fertilizer or plant protection, etc)? On which date it was given? What was the material information? For what purpose it was given? What was the rate and the amount of that farm input?

 

  • Add Pest/Disease Data: When any disease or pest attacks occurs the information regarding it can be stored here. The data such as the date on which the disease/pest was identified? Any information about the type of disease/pest? How much area got infected? Can add multiple images of the location that is infected. Can also add the location from where the images were captured.
  • Add Farmer Info: After geotagging a farm information apart from name, phone number, crop and area can be added in this section. The details such as address, village, talula, district, survey number, soil type, irrigation facility, crop to be grown, variety, expected sowing data, date of geotagging, total area sown, How much area sown of each crop (in case of multiple crop sown by the farmer), farmer code, land ID, farmers irrigation practices and all the related details to farming practices. Hence, the KYC is done fully.
  • Add Farm Advisory: To add personal advisory to the farmer this button can be used. The user can add an advisory to it and submit it. The advisory can also be added in pdf format which the system converts to images that can be easily readable by the farmers.
  • Get Satellite Data: This would provide you the satellite images of the farm by selecting the type of image you want to display and date for which you want the images. To visualize the image, you can select that image and click on Show to display the image. The images of various stages of crop can be seen such as NDVI, NDRE, NDWI, NDMI, EVI, SAVI, VARI, RVI, SOC, DEM, Evapotranspiration, TCI and ETCI.

The weather data can also be obtained from this tab. The weather data is obtained from the nearest weather station from the farm. When a user wants to share the satellite image/weather data it becomes difficult as he/she must copy the data in text format to send. But with the feature provided by Farmonaut, one can just click on the “Share satellite/weather” button which would convert the data into image format (Screenshot) within a few seconds which can be shared on any platform.

Web Application:

The data captured through the mobile application can be visualized in the web application as well. The changes/edits made are implemented to that particular login account.

When dealing with 5-10 farmers, the village area and other details can easily be obtained by searching on the application. However, when large corporations which deal with a large number of farmers (>500 farmers) have issues in navigating through the farmers. Hence, when the data is captured through a mobile app it can be visualized through the web app.

How to download farmers data?

Once the user login to the web application through the login credentials provided, he/she can download the data of all the farmers that are geotagged under that particular account. To download the data, click on the “Map Controls” button which will show up on the screen with the “Download Data” button. After clicking on it, all the data for all the villages associated with that account would be downloaded. The data is in .KML files and .XLSX file format which is downloaded in your Laptop/PC.

The downloaded excel data consists of overall information on the farmers who have been geotagged: includes Name of farmer, Phone number, Who has added that particular farmer, the ground team member who added the information, his phone number, the village, Field ID, Polygon ID, etc.

How to visualize multiple farms?

From the downloaded data, the Field ID can be copied or also can be typed on the screen. Field ID indicates the village the field exists in. Hence, when we enter the Field ID and click on the search button, at first the entire village would be visible. To see the fields that are geotagged within that particular village can be done by clicking on the “Display Field Polygons” button provided on the left hand side.

To get the information on any particular farm, just click on the field polygon.

How to add advisory at village/district level?

When there are more farmers associated within the boundary (let’s say 3000 farmers in a district), it would be feasible to set advisory for them at macro level. In order to do so, corporations can create advisory for primary crops in that area and then upload it through the application. Select the file of the advisory, it can also be previewed and then Click on Upload button.

CONCLUSION:

Farmonaut has developed an admin application for the large corporations for better management and quick process of the immense data of the farmers that are obtained. With this application, they can add new farms, visualize data, download multiple farmers data, Provide advisory services, get weather reports, visualize the satellite images and share the data to various platforms as well. The farmers being the ultimate beneficiary, the data to them are provided by the ground team which uses this application for geotagging and the office team uses it to navigate and provide advice to the farmers. Farmonaut has been providing these services to corporates such as Coromandel International, Troforte Innovations, Godrej Agrovet and many more.

LINKS TO:

Article: Admin App Tutorial

Video: Admin App Tutorial

FARMONAUT NEWSLETTER- SEPTEMBER 2022

NO MORE MANUALLY EXAMINING YOUR FARMS

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GET YOUR HANDS ON KNOWLEDGE ABOUT EMERGING AGRI-TECH

Decrease in the crop yield when compared to the investment made by farmers is a major issue. To overcome the issues Remote Sensing technology has been emerging in the Agri-Tech world. Farmonaut Technologies is helping businesses as well as farmers. Know how we are helping them in the Newsletter.

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Farmonaut started in 2018 with a vision to bridge the technological gap between farmers and bring the latest state-of-the-art technologies in the hands of each and every farmer in the most cost-effective way.

 

YOU WILL FIND HERE:

  • Emerging technologies in Agriculture Sector by FARMONAUT
  • What our clients/Farmers needs to know
  • Know the technology you are using
  • Providing Solution to the Businesses
  • Managing Individual Farms
  • Recognition and awards
  • Conclusion

Our Clients and Partners

EMERGING TECHNOLOGY IN AGRICULTURE SECTOR BY FARMONAUT

With increase in the advance technologies, the agriculture domain is booming at a high pace. Agri-Tech boosting over the past few years have found the solutions for the problems faced by farmers all over the world. Geospatial technology used in agriculture collects, analyses and stores geographic information. Due to which, the agriculture sector has been growing substantially. Remote Sensing (RS), Geographic Information System (GIS) and Global positioning system (GPS) are a part of the Geospatial Technology used.

Farmonaut Technologies uses this technology to help farmers. It was started with the vision to provide technology to each and every farmer in the most cost-effective way. It has been providing Satellite based Crop health Monitoring System, Voice and Text based plant issue identification and database to over lakh of farmers and various businesses based in India as well as in other countries. The services are easily accessible through web, android and iOS apps. For the convenience of farmers, it is available in 50+ languages.

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Remote Sensing is being widely used in agriculture to help farmers in monitoring the field through satellites. Farmonaut has come up with a cost-effective way to solve the farmers’ problems to a great extent without compromising on the quality of data. A detailed report is generated by the Farmonaut’s system does crop health monitoring of the field through the satellite data which gives away crop health, vegetation water stress and soil organic carbon. We have also been working with individual farm owners in different states of India.

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Farmonaut has also started providing various services to the businesses like providing database, GPS for fleet management, being API service provider, IOT devices for managing fields and Traceability of the product through block chain system. We have experience of working with International Corporates: Troforte Innovations, Textile Technologies Group Uzbekistan, Fair Climate Fund Netherlands, etc.

WHAT OUR CLIENTS/FARMERS NEEDS TO KNOW

With the emergence of Remote Sensing in agriculture, we are providing service to our clients and farmers for better crop yield and productivity in a cost-effective way.

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According to the research conducted, it has been seen that the productivity of crops has been decreasing over the years. This is caused due to improper management of the farmlands. The defects in the farmland and crops cannot be witnessed by the human eye and hence fail to take preventive measures.

 

Remote Sensing can be the key to the problems of farming. As it can be used for knowing the Crop Damage and Progress on a large scale as well as individual farmlands. Also, identifying the crop health through remote sensing would improve the production by controlling diseases and pests beforehand.

Apart from it, remote sensing can also be used for Crop Area and yield estimation which gives an upper hand in planning and resource allocation, evaluating prices and in decision making such as procurement, storage, etc. Soil Mapping is also possible with GPS.

Farmonaut is not only providing solutions to the problem of farmers through remote sensing but also helping them to cut down on the investment. An Indian farmer, on an average, spends between Rs.47,000 (580 USD) to Rs.350000 (4300 USD) annually on each hectare of arable land. By using Remote sensing the cost of labour, chemicals, insecticides, pesticides, plant growth regulators, etc. can be reduced up to 30%.

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KNOW THE TECHNOLOGY YOU ARE USING

Using the satellite data provided by Farmonaut in the form of comprehensible information, farmers can:

  • Reduce chemical/Fertilizer consumption by applying it only at the locations where crop health is in bad condition.
  • Reduce Labour costs by directing the labour only to the areas where crop health is low.
  • Reduce irrigation water wastage by knowing the water stress.
  • Increase the overall yield.
  • Maintain nutrient composition by knowing the soil carbon content.

Some of the concepts most commonly used for high level analysis by Farmonaut are NDVI, NDRE, EVI, VARI, SOC, NDWI, etc according to the use cases of each parameter.

For Crop health of crop at early growth stage

NDVI (Normalized Difference Vegetation Index)

NDVI is used as a measure to identify the state of plant health based on the light reflected by the plant at certain frequencies. Though we cannot perceive it with our eyes, everything around us (including plants) reflects wavelengths of light in the visible and non-visible spectrum. Taking into account how much of a certain wavelength is reflected, we can access the current status of plants.

EVI (Enhanced Vegetation Index)

EVI is further an optimized index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a decoupling of the canopy background signal and a reduction in atmosphere influences.

For Crop health of crop at later growth stage

NDRE (Normalized Difference Red Edge)

NDRE is a spectral index that helps in gathering the data at the later stages of a crop when chlorophyll content is relatively higher in the crop.

For irrigation:

NDWI (Normalised Difference Water Index)

NDWI index can help us control irrigation, significantly improving agriculture, especially in areas where meeting the need for water is difficult. The high NDWI values correspond to high plant water content and coating of high plant fraction, whereas the low NDWI values correspond to low vegetation content and cover with low vegetation. NDWI rate will decrease during periods of water stress.

Hence, through NDWI, the early detection of water stress can prevent many of the negative impacts on crops.

NDMI (Normalized Difference Moisture Index)

NDMI is used to know the moisture index / water stress in vegetation which helps in monitoring the drought condition of the areas. The kind of vegetation must be taken into account to further know the amount of water to use at particular growth stages of crops.

Evapotranspiration

Evapotranspiration measures the rate at which evaporation and transpiration occurs at multiple locations. Through evapotranspiration one can easily schedule the irrigation based on the indicators received by the data. Nevertheless, it can be ignored if NDWI and NDMI data result in a good condition.

For Advance Analysis

VARI (Visible Atmospherically Resistant Index)

VARI is minimally resistant to atmospheric effect, allowing vegetation to be estimated in a wide variety of environments. Hence, it is ideally recommended to be used for arm level decision making if TCI or ETCI images show visible atmospheric distortion such as mild clouds or haze above the field.

For Topography

DEM (Digital Elevation Model)

DEM is used to know the waterlogging prone areas in the field. During heavy rainfall or excess irrigation, the areas where the water logged or flood occurs can be identified through DEM. Hence, by knowing such areas the passage for the outsourcing of the water can be ensured by installing more motors in the area.

For Soil health:

SOC (Soil Organic Carbon)

SOC is a measurable component of the soil organic matter that indicates the better health and yield of any land once the cultivation process ends. Remote Sensing technology plays a vital role In enabling farmers to ensure high SOC content by taking the right measures at the right time and the right place. Farmonaut creates a SOC image with a colour map of the percentage of organic matter present in the selected field. The land area appears green in the colour map if SOC content is more than 5% and red if the SOC content is less than 1%. Once the locations with lesser SOC levels are identified by Farmonaut, farmers can get the soil testing done on specific regions, and the required actions can be taken.

For Crop health during Cloudy weather

RVI (Radar Vegetation Index)

RVI is measured by the backscattering which does not affect the data. The RVI data was designed to be the time series data which can be a great alternative to the NDVI. However, RVI can be obtained at extreme weather conditions when the satellite data could not be obtained due to cloudy or any other weather conditions. Hence, Farmonaut ensures the data at any conditions.

Farmonaut also provides RGB images of the field. (Coloured satellite images)

TCI (True Color Image): It is basically raw image of the field captured by satellite of a particular farm. This is not an index image, but a RGB representation of how the field looked like in human perceivable colors upon its last visit.

ETCI (Enhanced True Color Image): It is a TCI image processed by our own systems to enhance the land features which were not so explicitly visible in the raw TCI image.

PROVIDING SOLUTION TO THE BUSINESSES

Large-scale companies holding large hectares of land have trouble in managing them since manual examination would be a tedious and not accurate way for dealing. Hence, to help the businesses manage and increase the vegetation Farmonaut provides major market players service to make the businesses more efficient and convenient. They have been dealing with organisations in India as well as other countries of the world namely, Australia, Nigeria, Israel, Netherlands, etc.

To understand the working of it, mentioned below are the companies Farmonaut is working with.

GODREJ AGROVET

Godrej Agrovet has been working with Farmonaut since February 2021 in one state i.e., Andhra Pradesh. Presently working in 3 states namely Andhra Pradesh, Tamil Nadu and Orissa. They have already managed to map over 30,000+ hectares contributing to over 23,000+ field pieces.

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For the usage Godrej Agrovet needed to geotagged the farms in all the 3 states with Farmonaut’s field mapping platform for particular plantation. Using the Farmonaut admin application, the ground team managed to create the boundaries of the farms and also the KYC details of the farmers. Around 50 KYC parameters are captured such as Name, Phone No., Area, etc. They also capture the data points such as irrigation, survey no., taluka mandal, village, state, etc that helps to grade the farmers.

The geotagged areas can be monitored by the office team through web application. The farms can easily be monitored by the office team and help identify the gaps that indulge in the slow geo tagging process.

All of the system helps in knowing the number of trees in each and every farm. Counting of the trees or asking farmers doesn’t result in the accurate scenario and is a tedious task for large farmlands. There should be a certain number of trees per hectare. Hence to know the no. of trees in every farm, Farmonaut have their own system that uses high resolution satellite data.

The above image shows the area in which plantation has been carried out and the before and after images. The left-side image shows that the no. of trees was less and after plantation the right-side image gives the result after the plantation. The information such as No. of trees, area and Average/ha are provided on the top left-corner of the image.

With this information the farmers can be informed about the areas where the plantation hasn’t been done. Due to which, the manual labour work reduces, increases the accuracy and ensures the data at faster rate.

To decide the care that should be given to the plantations majorly would depend upon the age of the plantations. Different age plantations such as young, nature, old, very old need different care. Using the Farmonaut high resolution satellite data up to 3 meters and 10 metres helps to identify at what farm what is the average tree age. Hence, the team can direct the farmers on what care should be given to the plantation.

Farmonaut platform also screens out geotagged fields where there are no palm plantations.

ITC LIMITED

ITC started in 1910 as India’s foremost private sector company. It has diversified over years into different sectors from FMCG to agribusiness with 13 businesses in 5 segments. With different sectors, it has been dealing with farmers as well.

To initiate, recently Farmonaut have started assisting farmers for better improvement in farming practices. This has started as a pilot project for paddy fields for upcoming large scale projects for all farmers joined with ITC Limited. They have been assisting multiple FPOs (Farmers’ Producer Organisation) aligned with ITC. They have started to use the technology in the 4 states: Maharashtra, Madhya Pradesh, Uttar Pradesh and Rajasthan.

The ground team of FPOs visits the farms in order to capture the location of the field and geotag using the Admin application. The data such as farm area, Name of farmer, Contact, etc is also captured by the team.

Through this information and the field captured, the farms are monitored continuously for the crop health, soil health, crop irrigation, weather, etc. The system also generated reports constantly at regular satellite visits. The data captured are advantageous for advising the farmers for action to be taken. Hence, the prior actions would be beneficial to farmers in decreasing losses and increasing overall yield.

FASHION FOR BIODIVERSITY

Fashion for Biodiversity being the organization that deals in the cotton requires to track the data as well. In order to track the data of the field they procure, Farmonaut has been providing satellite crop health monitoring as a solution. The farms are first geotagged and submitted to the Farmonaut’s system. The data such as crop health, water stress and carbon content are obtained from the satellite. These data are generated automatically through the system, which helps to know the irrigation required, fertilizer applications and various other factors to take precautions for better crop yield.

Farmonaut‘s manufactured IOT devices are installed in the farms that are managed by the Fashion for Biodiversity team. The IOT devices are capable of capturing various data of the farm areas. The data captures are weather parameters and soil parameters. The weather parameters such as leaf wetness, wind intensity, air temperature, air humidity, light intensity, CO2 and wind direction. The soil parameters that are useful are captured like Soil temperature, soil pH, and N, P, K electrochemical conductivity.

The data collected are sent at an interval of 5-15 minutes. The data gained are visualized on the dashboard of the Fashion for Biodiversity. Hence, being a company dealing specially Cotton helps them navigate the parameters through the crop cycle as well as know the defect areas. The satellite as well as IOT device data used in combination helps in getting the precise results that would be helpful in increasing the yield and productivity of the cotton over seasons.

 

Farmonaut has also been providing the Traceability of the entire Supply chain of cotton. Fashion for biodiversity goes through various steps after the harvest of cotton to obtain the finished product. The process by which the cotton is manufacture is as below:

Cotton is procured from the farmers

Sent to Ginning process

Sent to Spinning process to produce Yarn

Sent to Weaving process

CMT (Cut Make Trim)

Sorting of finished garments

Warehouse/Retailer with lot numbers

At every stage of the process mentioned above Farmonaut helps them to capture the details of the transportations. When a lot of cotton is sent to various stages it is tracked throughout the process and details such as from where the item was picked up, from where it was held and where it was dropped would be stored. The traceability is based on the block chain, which has potential to track the fake transactions, product origin and rectify the outbreaks. Due to this Blockchain based traceability has advantages of being flexible, track the back data and also maintain the authenticity of the data.

COROMANDEL INTERNATIONAL

Coromandal based in TamilNadu started in 1906 with a vision to be the leader in providing farm solutions with strong commitment towards sustainability. They have been providing various farm inputs such as fertilizers, nutrients, crop protection, seeds, farm implements, etc. Apart from this, they have also started farm services for farmers which includes Testing services for soil, crop advisory, Ag Tech, etc.

To deliver the crop advisory to farmers, Coromandal has adopted the services from Farmonaut through an API system. To enable the data for a particular farmland, the area of the farm must be submitted in the system through the geotagging feature provided. Coromandal has to map the farm boundaries of their farmers in order to obtain the data.

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Once the area is geotagged, the system generates the data through satellite images that are obtained every 3-4 days. The data generated report of the farm contained various parameters (18 different satellite parameters) on weather, soil, etc. through this data the advisory to the farmers is given by the Coromandel team.

Soil organic carbon being the most important factor for the enhancement of the crop growth should be taken care of. Farmonaut is also providing soil organic carbon data in order to maintain the fertility of the soil. By knowing the time series data of soil organic carbon, the farmers can be advised on what nutrients are deficient in the soil which are required for better yield of crops.

KISANWALA

Kisanwala is a company based in Hyderabad, with a vision to help farmers with end-to-end solutions for all farm needs by providing technology, information, inputs and support. Their services range from advisory, agronomy, forecasting to providing support at input and output level.

Using the API system from Farmonaut Technologies. Kishanwala has been providing Forecasting services in order to advise the farmers on weather conditions and better crop growth and yield. Farm area of farmers associated with Kishanwala are geotagged on the maps. The satellite data for the areas are generated automatically by the system. The data consist of various information such as temperature, humidity, soil pH, soil moisture, crop health, etc.

Based on the data received from the satellite the Farmers are advised what precaution or action that must be taken for better yield and crop growth.

FAIR CLIMATE FUND

Carbon Emission is the amount of CO2 that has been released in the atmosphere due to certain activities. Carbon Emission has been increasing tremendously in the past few years. Due to which immense impact on the environment and agriculture farms is seen.

To control the emission and save the environment, international treaties have come up with a concept of carbon credits. Carbon credits are a kind of validation to release carbon upon permissible limits. When a company/business claims to release only a certain amount of carbon but due to several reasons want to release more than desire. In such cases the company purchases carbon credits. One carbon credit allows one tonne of CO2 or equivalent amount to greenhouse gases in the atmosphere. These exchanges in credits have encouraged carbon trading worldwide. These credits can be exchanged between businesses or bought and sold in international markets at usual market price at two exchanges, namely the Chicago Climate Exchange and the European Climate Exchange.

Carbon Emission can occur at any level, from the energy sector to agriculture sector as well. Soil has its own carbon content which has its importance for soil fertility and health. To know the soil carbon content would help to track the declining CO2 that has destroyed or gotten into the atmosphere.

Fair Climate Fund based in the Netherlands has initiated a contribution to the healthy environment. Hence, they have started mapping the field in North India to estimate the carbon emission and carbon content in the farms. The Farmonaut system helps to track the carbon content over the seasons. The Fair climate fund has reduced around 716 thousand tonnes of CO2. There are many ongoing projects in different parts of the world by the Fair Climate Fund.

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TTG (TEXTILE TECHNOLOGIES GROUP), UZBEKISTAN

TTG being a company in Central Asia has been producing Yarn since 2014. They export yarn to many different countries in the world. TTG is providing benefits to its customers by excellent quality, fast shipping, affordable prices and Contract work.

TTG, Uzbekistan

Dealing with different situations towards farming, TTG either takes farms on lease from the government or acquires the farms from the farmers who have already been taken on lease. In some cases, TTG also helps farmers in farming practices or provides a team for carrying out the farming operations. However, the farmers are paid throughout the crop cycle.

Issue faced:

Farmers working for the company get paid based on the claims made regarding the requirement for farming. Due to which when the investment made by the company gives lower yield than expected indicates loose ends in the stages of the process.

WHAT CAN BE DONE?

To fix the loose ends and to provide solutions to the TTG company, Farmonaut Technologies have been working with them for a year now. Uzbekistan deals with regions and clusters similar to talukas and districts in India. Where every region has its own regional leader.

First, the farms under the TTG company are geotagged into the systems. The satellite data of the farms are generated frequently. The system creates a report for the farm which contains information on various parameters such as carbon content, irrigation, soil moisture, soil pH, temperature, humidity, etc. The report generated is in Uzbek, a language of Uzbekistan. Using the satellite, they can easily track and inspect at region level, cluster level or farm level.

To briefly describe, the information such as how much area requires irrigation, which area has enough moisture, area that is performing bad, the fertilizers requirements in the areas. Using the automatic generated reports, they can examine the areas. These parameters in the reports helps to know the defective areas and the problems faced can be informed to the region leader whomsoever the area belongs. To be precise the reports give information to close the loose ends and help TTG to save from the major capital losses.

Fleet management

In order to manage the machinery used in farming practices, GPS devices are installed with machines. GPS then is directly linked to the Farmonaut systems to motion track the machinery. The system also captures the information of the farmers such as Name, Phone number, farm area, etc. The system then creates the insights of the machinery.

The insights of machinery consist of:

  • How much area was covered
  • Distance travelled
  • Total cumulative area machine visited
  • Number of farms visited
  • Time spent on each farm
  • How much time the machine was working

Significance:

Knowing the insights of the machines, it can be effectively managed by decreasing the non-required activities. Also, any defect in the machine can be identified by the insights of the machines.

Due to this feature provided the mismanagement of the tracking fuel can easily be caught. The insights not only help in tracking fuel consumption but also in various aspects such as whether a farm visit is done or not, how much time was wasted in different activities, etc.

ZR3I

Zr3i started in 2020 with an objective to provide the modern technologies to the agricultural organization that would help in better managing of their fields. Zr3i has been providing their services to farmers, agribusinesses and workers who need the services. They have developed a website and an android application for Egypt and the Arab World which is provided in Arabic language for better understanding of local farmers. The application works on API between Zr3i and Farmonaut Technologies.

The problems faced by farmers such as incognizance of weather parameters and soil parameters leads to decrease in yield as well as profits. The major problems faced are Water Stress, Carbon level and usage of chemicals.

To overcome the problems and help farmers, Zr3i users are provided detailed reports on their farm condition by Farmonaut. The reports are generated by the use of satellite images which contains information on crop health and weather conditions of farms. The satellite images are easy to interpret through the colours. As the red area represents barren land, the yellow area requires more attention as it can be affected more and the green area is in good health condition. The satellite images generated are NDVI, EVI, AVI, SAVI, NDRE. NDVI, EVI, SAVI and AVI images helps at the early growth stage of crops whereas NDRE images are used at the later stage of crop growth. The reports also contain NDWI images that monitor the water content and help control irrigation. To add upon the system also provides carbon content and time series data as well as precise information as per the data points provided by the user. Along with this it also gives field images based on longitudes and latitudes with the historical data of their field.

Zr3i has been reaching greater heights being the first SaaS digital platform in the Arab World. It has also been recognised at the regional level across the Arab World.

AGRO DRONE

AgroDrone is an Israel based company dealing in UAVs (Unmanned Aerial Vehicles commonly known as Drones). Specifically, it deals with drones in agriculture for farmers to know their farm better. For large farmers in Israel with land holding more than 100 hectares, AgroDrone has been working to help farmers through Drones and satellite images as well.

Drones alone faces various disadvantages:

  • Requires trained operators
  • Less flight times
  • Less range
  • More featured drones
  • Can cause accidents
  • Difficult to operate

To overcome the disadvantages, Farmonaut Technologies has been providing the satellite data that captures farmland. With the help of this technology, the crop health parameters are known to farmers for better crop yield. The usage of drones in combination with satellite data for the farms is adopted by Agrodrone. This approach is called the Hybrid Approach.

The data collected from the drones were not enough to know the condition of crops due to its limitations. Instead of flying the drones over the whole field, the satellite images would indicate the areas that require focus and field visit to improve the conditions. After which the drones would only be flown over the infected/high risk areas which would be helpful in overcoming the major problems faced by drones.

TROFORTE INNOVATIONS

Since 2021, Troforte Innovations have started providing services with Farmonaut Technologies for farmers in Australia and NewZealand. Australia being the world’s major contributor to agriculture has farmers with large land ownership which varies from 100-1000 hectares. Supervising such large farms is tedious work and results in inaccuracy.

To manage the farmlands, Farmonaut is providing service to Troforte Innovations through API. The system provided is Crop health monitoring with Satellite. This system helps the farmers to know the condition of their crops and overall health of the soil and crops. The satellite data is obtained by the NDVI which uses red visible and infrared rays. The data obtained includes:

  • Crop health
  • Evapotranspiration
  • Soil Moisture
  • Water Stress
  • Soil organic carbon
  • Current & forecast Weather

The data obtained through this would help the farmers to know the sudden changes in the farm due to weather, temperature, etc. Soil Moisture data would direct the farmers to the areas that require irrigation and areas that are over irrigated. Further it would also indicate the high amount of fertilization used. The crop health data indicates towards the infections and diseases caused in crops to take precautions beforehand.

Farmers in Australia are more aware of soil health and hence Troforte Innovations does provide soil sampling services to farmers for better crop conditions. The soil testing goes through the following process which would help farmers in improvement of the crop yield and productivity.

1. COLLECTION OF SOIL: The farmer must collect the soil from his/her farm from different locations in the bags. The bags provided have barcodes with 8-10 digits on them for digital use.

2. FORWARD THE SAMPLES: The bags are sent to the soil testing Labs.

3. TESTING THE SOIL: Soil testing Labs performs multiple tests nearly 10-15 tests. The tests help to identify various parameters such as pH, EC (electric conductivity), Carbon content, Saturation percentage and Nutrients like Potassium, Nitrogen, Magnesium, Phosphorus, etc.

4. UPLOADING THE RESULTS: After testing the results are stored in a system created by Farmonaut Technologies. The Labs pushes the tested results to the Farmonaut’s internal system through an API system. The API system is used by the third party to upload data to provide them to the endpoint (in this case the endpoints are farmers).

5. EASY ACCESS TO RESULTS: The access to the soil tested data can be gained by scanning the barcodes on the bag. The results are on the farmers mobile for their convenience.

SOPA (SOYBEAN PROCESSORS ASSOCIATION OF INDIA)

SOPA has been performing Crop Area Estimation in 50 districts of Madhya Pradesh, Maharashtra and Rajasthan. Soybean being the high valued oilseed crop requires information on the crop production to understand the crop sown. For the estimation of crop area and yield, optical remote sensing data source was used. Crop leaves being sensitive to the visible and infrared regions helps to estimate accurately. With the help of optical satellite images and Synthetic Aperture Radar (SAR) the kharif season crop could be mapped. SAR has the ability of operating wavelengths that can access data during cloud cover too.

This estimation method helped SOPA to determine Crop Area Sown, Crop Identification, Tracking of Sowing and harvesting patterns of the producers. All this information helps them in suggesting the prices of soybean oilseeds, export/import decisions and storage and distribution of oilseeds.

LINXAG (LINX SPATIAL SYSTEMS)

The tremendous increase in the businesses have evolved in the past few years. LinxAg based in Nigeria has developed a web app and mobile application called as Bizterrain for the small scale as well as large scale businesses.

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The app is capable of capturing the data using the mobile application such as boundaries of the business location, shops, name of the owner, contact No, etc. the capture can be accessed by any user of the application very conveniently. In case of any changes taking place in location or any other details of the businesses the details can also be edited with ease.

The mobile application is flexible and is capable of doing all the activities i.e, capture, access and edit data.

The web application is not able to capture the data but can easily access the data and edit the data.

The application provides 4 tabs: Dashboard, Analytics, Report and Profile.

Use Cases of the Application:

Government:

In case the government wants to initiate a scheme and select the criteria for the scheme. This app will be useful to know the profiles of the people and hence will be helpful in estimation of the people eligible for the scheme. For example: if governments want to initiate a scheme for women, they can find the estimate on how many women are there in the region in particular eligible for the scheme.

Similarly, if the scheme is introduced for farming businesses, the app will be useful to know no. of businesses involved with farming/farmers.

Large Company Owners: 

Large companies have major benefits using it as they can collaborate with small business owners at reasonable cost. For example, if a large clothing brand wants tailors in the region, they can easily get access to the contacts of tailors and initiate collaborations at local price points.

With the filter feature it becomes more convenient for the user to find the required contacts. The location shown on the map would be useful in case of excess inventory to store at the warehouses at different locations.

Small Business:

Small businesses can register their profile and get opportunities to collaborate with large businesses which would give them a passive income at better cost.

MULPURI POULTRY:

Mulpuri Poultry are the 2nd largest producer of eggs in India based in Guntur district of Andhra Pradesh. Poultry mainly requires two types of feed, soybean and maize. Due to the highest no. of poultry animals, the feed required would be in bulk and hence cost would be high.

Farmonaut has been working on crop area and yield estimation for Mulpuri farms for an objective to strategize poultry feed aggregation. The estimation would help them to know the expected yield in the particular area for further estimation of prices. If the sowing area of maize is large, the supply of maize would be high and as result the prices would be low. Simultaneously, if the area sown is small, the supply of maize would be less and eventually results in high prices. Hence, the information helps them to decide which kind of feed would be fed for poultry.

Presently, the decision for feed is done for one feed, with a future objective to expand it to 18 feeds.

FARMER AMIGO

Farmer Amigo is an Agri-tech start-up which helps farmers by providing door-step deliveries of seed-to-market to millions of Indian farmers through technology.

In collaboration with Farmonaut, Farmer Amigo is using the API system through Farmonaut in order to provide solutions to the farmers. The company uses the geotagging method to locate the farmland of farmers throughout Maharashtra. The data are received on the system and the system automatically generates the reports of the farms geotagged.

The reports generated are used to manage the farms of the farmers and also advise them on the crop health issues and irrigation practices. The reports contain many information parameters such as weather parameters, soil parameters, etc.

API USERS:

IVD Digital, Crop United and UBINCORE are companies working closely with farmers. For the betterment of farmers, they have been using the Farmonaut API system to provide solutions to the farmers in a cost effective way. The increasing investment in farming has caused a major issue for the farm owners.

The companies can locate the farmland of their users through the admin application provided by Farmonaut. After the geotagging is completed, the system automatically generates the report of the particular farms. The report is completely based on the satellite images collected from the high-resolution satellite.

There are various parameters that have been examined and also the historical data of the same are available to make the decision for the better yield and growth of crops. Crop health monitoring and soil monitoring gives the companies a better idea whether what care must be taken or what can be done to improve the vegetation.

MANAGE YOUR INDIVIDUAL FARMS

Individual farmers face some issues regarding the crop diseases, irrigations, etc. which cannot be identified beforehand. In order to manage farms and know the problem caused, visiting farms isn’t possible every time. To overcome it, Farmonaut is also providing their remote sensing technology to individual farmers as well.

Some of the individual farms are mentioned below:

VISWAMATHA FARMS:

Viswamatha farms located in Andhra Pradesh, has been passionate about the zero-budget natural farming and natural farming techniques. This Natural farming is done without chemical usage which leads to no greenhouse gas emission. They believe that natural food tastes great, is of high quality and full of nutrients which eventually gives good health and environment.

In parallel to the natural farming practices, Viswamatha farms has also been referring to the satellite data provided by Farmonaut through our platform (available on android, iOS as well as web app) to take field level actions and minimize the efforts even further, since 2019.

No photo description available.

No photo description available.

In the above image is of Viswamatha farms where the top portion of the field shows good water stress in vegetation. The yellowish or red region in the remaining field shows that the region must be irrigated by the farmers or at least requires a visit for cross-checking.

VAIVIDHYA FARMS

Vaividhya farms located in Andhra Pradesh have been using the Farmonaut satellite crop-based monitoring to enhance the growth of the crops. The system matches the location of the farm and satellite coordinates which helps in fetching the latest images. This image helps in identifying the regions of unhealthy growth and help the farms to take precautions beforehand. It also indicates the water stress and organic carbon content. Vaividhya farms have managed to better crop health in a period of 1 month by using the Farmonaut Services.

DISEASE FREE LIFE

Ranga rajan, a farmer based out of South India has colorblindness which makes it difficult for him to identify the satellite images. The colour-blindness is faced by many farmers in India. Colour-blindness can be of many types. Farmers with this disease would have difficulty in interpretation of the satellite images. In this case, the farmer wasn’t able to differentiate between the colours such as green, pink, yellow, orange, etc. The colour-based depiction is the most recommended because it is found to be the easiest for farmers to differentiate areas aptly. The red represents danger and green for the areas in good condition.

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For colour-blind farmers, Farmonaut has built a unique system which is encoded to interpret the data to colour blind variation. The data of crop health and irrigation were combined and created as black and white images. No matter what type of colour blindness a person has, he/she can always differentiate the black and white colour. They may or may not be able to identify other colours. On the Farmonaut app the data are available under the Colour-blind Visualization.

The black and white images obtained represents:

  • Black: the area requires a visit to the farm to check the crop health or irrigation issues.
  • White: area has the irrigation issues only
  • No colour: the area is in good condition

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RECOGNITION AND AWARDS

Farmonaut has been recognised by the Government itself as a startup for digital agriculture. The report “Agriculture situation in India” published in May 2021 by various government departments gave recognition to Farmonaut as a startup that is building bridges between the farmers and technologies that must strive with each and every farmer.

It is a pleasure to announce that Farmonaut is also recognised and selected to be the part of the Jiogennext ecosystem.

Farmonaut was introduced as a startup using the geospatial technology to help cut down on the investment on farm inputs, and enabling them to increase the yield.

Apart from recognition, Farmonaut has also received awards such as:

  • “Most Admired & Preferred Agritech Emerging Unicorn Award for the Ground-Breaking & Innovative Technology” at 127th Conference.
  • 2021 CEO Awards held on 27th August at Aloft Cessna Business Park, Bengaluru organized by CE Worldwide.

Farmonaut also participated in the panel discussion “Riding the Digital Wave…How high-speed Internet is changing the content that people are going to be consuming?” and share our thoughts on how the farming industry will change as a result of high-speed internet.

The Prestigious Ramaiah Evolute Star Startup Award was also received by Farmonaut for their recognition of the best cross-disciplinary start-ups using high technology and innovation which results in a significant impact on the society.

Samashti Foundation organised a tree plantation initiative at Hunasavadi on 15th June with over 5000+ trees planted.

For the smart care of the farms and plantation by farmers, Farmonaut will be monitoring the areas of plantation through satellite technology for their health by multiple parameters.

Farmonaut was pleased to be a part of it.

CONCLUSION

Evolving Agriculture with different technology has made farming hassle-free worldwide. With India ranking at 2nd in the world agricultural sector, it requires additional effort to make it easier for the farmers. Farmonaut is penetrating into the Indian market as well as international market with the remote sensing technology providing various services such as Crop health, Soil health, Traceability, API Access, Crop Area and yield estimation, Tree number and Age estimation, etc. making it accessible to small farmers as well.