Inter Islamic Network on Space Sciences and Technology


  • Azerbaijan
  • Bangladesh
  • Egypt
  • Indonesia
  • Iran
  • Iraq
  • Jordan
  • Libya
  • Morroco
  • Niger
  • Pakistan
  • Saudi Arabia
  • Senegal
  • Sudan
  • Syria
  • Tunisia
  • Turkey

Technical Projects / UAV based Digital Farming for Enhanced Productivity & Food Security

 UAV based Digital Farming for Enhanced Productivity & Food Security


  1. Overall Objectives: Smart farming solution for better crop yield estimation, health assessment and growth monitoring employing aerial platforms in a network
  2. Project Details:
    1. This proposal focuses on the enhancement of farm productivity and quality while reducing the resources by using modern technologies leading to better food supply and security. The focus is to develop an end to end solution for farmers so that the system may be deployed with minimal training and infrastructure by using intelligent algorithms.
    2. In order to optimize per acre yield of a crop, regular monitoring of crop's health and fields composition is required for taking appropriate measures in case of any abnormality is observed. For crops spanning over a large area, monitoring is difficult and a labour intensive task. With the result, crops are prone to damage due to lack of timely remedial measures.
    3. The proposed system will collect optical and multi-spectral data of crops and fields through fleet of Unmanned Aerial Vehicles (UAVs). The UAVs will coordinate to make effective path planning for scanning larger agriculture fields. Ultimately, this approach allows more data to be acquired faster, with less effort.
    4. The proposed solution will also employ Internet of Things (IoT) based well-distributed field sensors on ground to monitor soil condition, weather, crop health status and to make data logs. These field sensors are in contact with soil or at a very close range which would help in soil characterization. Cognitive IoT solutions can sense all these data and provide strong insight to improve yield.
    5. Crop monitoring and field status will be realized through AI based smart solutions using deep learning algorithms. The developed algorithm will process and analyse high-quality, multi-sensor data obtained from optical/multispectral payloads for better crop yield estimation, health assessment and growth monitoring. The proposed intelligent solution will enable farmers for timely detection of any impending anomaly on a regular basis to enable optimization of returns and preserving resources.
    6. The proposal consists of a decision support system comprising data processing and management as well as an end user terminal for data products provision. This will allow users to monitor and plan agricultural cycle more efficiently by taking timely actions and applying fertilizers, pesticides and other resources intelligently using geospatial information of crops.
    7. The project will provide critical information to increase crop production, health monitoring and controlled utilization of resources to maximize the productivity and ensure food security in the country
  3. Expected Benefits: The project will lead to increased farm productivity and quality as well as improved working conditions through reduction of manual labour. Intelligent decision making will improve by the time when more data will be generated by aerial and ground sensors. As the progress continues, it will become more sustainable against varying field and weather conditions across the country. In the next phase field equipment may also be deployed for different crop stages further reducing the resources. Subsequently conventional systems will be replaced by modern state of the art practices.


Home    |    ISNET    |    Activities    |    Membership    |    Miscellaneous    |    Contact

Copyright � ISNET. All Rights Reserved.