Extend your horizons with drone-powered solutions to spend less and earn more!

Revolutionizing Agriculture with Drone Powered Solutions

Drone technology has left a long-lasting impact on the Agriculture industry of India and its efficiency. We present drone-powered solutions to farmers to increase productivity in crop monitoring to planting, Livestock Management, Pesticide Spraying, Crop Stress identification, Treatment Planning, Plant Growth Monitoring, Precision Farming, Scouting and much more.

We use high-tech Aerial Surveying drones equipped with advanced sensors, such as RGB and Multispectral Sensors , to procure precise data. Drones such as DJI Inspire 2 accumulate high-resolution crop data to identify any issues with the crops and notify them for immediate action before damage occurs. Geo-tagging Aerial Images provide valuable information that reduces cost and boosts yield by a significant percentage.

Advanced drone technology and Machine Learning for Precision Agriculture result in improved crop yields and profitability. Correspondingly, lower levels of standard input from the farmers are required to grow crops and maintain land, water, fertilizer, herbicides, and insecticides.

We combine UAV Aerial Imagery with Machine Learning systems for Crop yield forecasts, accurate crop count, crop emergence analysis, irrigation monitoring, crop health, crop damage assessment, field soil analysis, etc. High-quality drone data and Photogrammetry guard crops to guarantee productivity and to equip farmers with all benefits accessible.

Benefits of Drone in Agriculture with Tensa Labs Drones

  • Higher-resolution visual inspections with drones compared to ground-based inspections
  • Increase efficiency with high-resolution data in a very timely manner with thermal/4k capabilities
  • Farmers make better decisions and avoid costly mistakes with aerial mapping of crop fields.
  • Save cost, time and resources with Drone Mapping for your Crop fields compared to ground-based approach
  • Highly accurate Predictions for - inventory information, crop emergence, drive replanting decisions, total yield prediction, etc

Deliverables We Offer

Digital surface model (DSM)

Digital Surface Models (DSMs) are Digital Models embodying elevations of the field and vegetation in agriculture. They are used for various purposes such as irrigation planning, water flow analysis, and crop optimization based on slope direction. Our drones equipped with low-altitude remote sensing (LARS) cameras can acquire RGB images in a high spatial resolution superior to the data obtained through traditional means.

Example of Vegetation Index Map

Maturity indices decide when a crop should be harvested and ensure that satisfactory consumption meets the consumer. Vegetation indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge (NDRE), chlorophyll-based indices, SAVI, OSAVI, and other index recognize and quantify any differences in the field. With technology sensing, it is quick and easy to visualize and detect such variability. Using UAV technology, we can create farm field health maps from visual and multispectral aerial imagery for thorough analysis.

False-color band combinations

DDrones equipped with Multispectral Sensors can support visual combinations of red, green, and blue colors. These combinations and algorithms are dependent upon the phenomenons of reflectivity and absorption at multiple wavelengths. The different patterns allow us to see distinct features of hidden plants and risks like the presence of weeds or water-logged soil that would otherwise not be visible.

Fields Orthomosaic Map

Time is said to be a farmer's most valuable resource. They need to be able to detect damages and resolve problems in their early-stages for the utmost efficiency. A precise color Orthomosaic Map is often the first step and most crucial step in scouting. With the help of interpretation, farmers will be able to detect gaps in the crop instantly and find areas of visible stress while visualizing the maturity and growth stages of their vegetation.