Title: GIS-Based Solar-Powered Drone-Based Weed Cutter for Lake Management. Project Location: Faculty of Fisheries Rangil, Shere-Kashmir University of Sciences and Technology Contact Information: 7006386878, Email. id: agaashfauq@gmail.com Project Budget: Rs/=20,0000 lakh Project Team: P.I 1. Dr. Ashfauq Farooq Aga Assistant Prof cum Scientist Aquaculture Engineering Division of Fishery Engineering Faculty of Fisheries Engineering, Rangil, Ganderbal Shere-Kashmir University of Sciences and Technology CO-PI: 2. Prof (Dr) Gohar Bilal Wani Professor (Aquaculture Engineering) Division of Fishery Engineering Faculty of Fisheries Engineering, Rangil, Ganderbal Shere-Kashmir University of Sciences and Technology CO-PI: 3. Prof/ (Dr) Farooz Ahmad Bhat Head fisheries resource managment Rangil, Ganderbal I. Project Summary: Aquatic weeds and invasive plant species can rapidly spread in lakes, ponds, and other bodies of water, causing numerous ecological and environmental problems. These weeds can disrupt the natural balance of aquatic ecosystems, reduce water quality, and limit recreational activities such as swimming and boating. Traditional methods of weed control, such as herbicides and manual removal, can be expensive, labor-intensive, and environmentally harmful. • The use of drones equipped with cutting tools offers a promising solution for efficient and eco-friendly aquatic weed management. Integrating Geographic Information Systems (GIS) technology into this approach can significantly enhance the effectiveness of weed cutting by providing real-time data on weed distribution, growth patterns, and the overall health of the aquatic ecosystem We propose to develop a solar-powered drone-based weed cutter system to effectively manage aquatic weed growth in lakes. This innovative solution combines advanced drone technology with Global Satellite Imaging (GSI) for real-time monitoring and precise weed cutting, reducing the environmental impact and operational costs associated with traditional weed management methods. The project aims to improve water quality, enhance aquatic biodiversity, and promote sustainable lake management. Develop an autonomous weed cutter system capable of navigating lakes and efficiently cutting aquatic weeds. • Integrate GIS technology to create a comprehensive mapping and monitoring system for weed infestations. • Enhance environmental sustainability by minimizing the use of herbicides and preserving native aquatic flora and fauna. • Improve water quality and recreational experiences in lakes. II. Objectives: 1. Design and build a solar-powered drone equipped with weed-cutting mechanisms. 2. Integrate GSI data for accurate weed detection and monitoring. 3. Develop an automated weed-cutting algorithm for precise and efficient weed removal. 4. Implement a user-friendly interface for remote operation and monitoring. 5. Conduct field trials to assess the system's effectiveness and efficiency. 6. Create a sustainable business model for the long-term maintenance and operation of the system. 7. Design and build a drone-based weed cutter system capable of autonomously navigating lakes and cutting aquatic weeds. 8. Develop a GIS-based monitoring system to collect and analyse data on weed distribution and lake conditions. 9. Implement real-time decision-making algorithms to optimize weed-cutting routes and prioritize areas of high weed density. 10. Evaluate the environmental and economic benefits of the drone-based weed cutter compared to traditional weed control methods. 11. Integrate GIS technology to create a comprehensive mapping and monitoring system for weed infestations. 12. Enhance environmental sustainability by minimizing the use of herbicides and preserving native aquatic flora and fauna. 13. Improve water quality and recreational experiences in lakes. III. Project Components: 1. Drone Design and Development: • Custom drone design and construction. • Integration of a solar panel system for energy-efficient operation. • Installation of weed-cutting mechanisms and sensors. 2. GSI Integration: • Access and utilize GSI data for lake monitoring. • Develop algorithms for weed detection and mapping. 3. Automated Weed Cutting Algorithm: • Design and implement an algorithm for autonomous weed cutting. • Ensure precision and safety in weed removal. 4. User Interface: • Create a user-friendly interface for remote operation and monitoring. • Enable real-time feedback and control. 5. Field Trials: • Conduct field trials in multiple lake environments. • Gather data on system performance, weed removal efficiency, and environmental impact. 6. Sustainability and Business Model: • Assess the economic feasibility and sustainability of the system. • Develop a business model for maintenance and service provision. Methodology: • Hardware Development: • Design and construct an autonomous weed cutter equipped with GPS, sonar, cameras, and cutting mechanisms. • Implement obstacle avoidance and navigation algorithms. • Software Development: • Develop a GIS-based mapping system for real-time monitoring of weed growth and infestation levels. • Integrate machine learning for image recognition to identify target weeds. Testing and Validation: • Conduct field tests in various lakes to evaluate the system's efficiency and accuracy. • Collect data on weed distribution, water quality, and ecosystem health. • Project Budget: A detailed budget for the project will be developed as part of the initial project planning phase, including costs for materials, equipment, personnel, and any other relevant expenses. • Item • Estimated Cost (RUPEES) • Research and Development • 500000 Lakh • Hardware Components • 600000 Lakh • Software Development • 500000 Lakh • Field Testing and Evaluation • 50000 Lakh • SRF, JRF (salaries, benefits) • 200,000 Lakh • Miscellaneous (contingency) • 150,000 Lakh • Total Budget • 20,00,000 Lakh IV. Project Budget: The estimated budget for this project is as follows: 1. Drone Development and Integration: 5.0 lakh 2. GSI Data Access and Analysis: Rs/=5.0 lakh 3. Automated Weed Cutting Algorithm: Rs/=6.0 lakh 4. User Interface Development: Rs/=1.5 lakh 5. Field Trials and Data Collection: Rs/=50 thousand 6. Sustainability Planning and Business Model Development: Rs/=50 thousand 7. Miscellaneous Expenses (contingency): 1.5 lakh Total Project Budget: RS/= 20,0000 Project Tasks: The project will consist of the following major tasks: 1. System Design and Development: • Design the drone-based weed cutter system, including the cutting mechanism, propulsion system, and control software. • Integrate GIS technology into the drone system to enable real-time data collection and analysis. 2. GIS Data Collection and Analysis: • Collect baseline data on weed distribution, water quality, and lake topography using GIS techniques. • Develop algorithms to analyse and visualize the collected data to make informed decisions on weed cutting. 3. Autonomous Navigation: • Implement GPS-based navigation for the drone to autonomously traverse the lake while avoiding obstacles. • Develop obstacle detection and collision avoidance systems. 4. Weed Cutting Mechanism: • Design and build the cutting mechanism, ensuring it is safe for both the environment and wildlife. • Test and optimize the cutting mechanism for efficiency. 5. Real-time Decision-making: • Develop algorithms to prioritize areas for weed cutting based on GIS data and real-time observations. • Implement adaptive route planning to optimize the drone's weed-cutting path. 6. Testing and Evaluation: • Conduct field tests to assess the performance of the drone-based weed cutter. • Compare the effectiveness, cost-efficiency, and environmental impact of the drone-based system with traditional methods. 7. Documentation and Reporting: • Prepare detailed documentation, including system specifications, user manuals, and research reports. • Present project findings and recommendations to stakeholders. • Project Deliverables • The project will deliver the following key outcomes: • Drone-based weed cutter prototype with GIS integration. • GIS-based monitoring and decision support system. • Field test results and performance evaluation reports. • Documentation and user manuals for the system. • Presentation and reports for stakeholders and project sponsors. V. Expected Outcomes: 1. A solar-powered drone-based weed cutter system capable of efficient and precise weed removal. 2. Integration of GSI data for real-time lake monitoring and management. 3. Improved water quality and aquatic biodiversity in target lakes. 4. Reduction in operational costs and environmental impact compared to traditional methods. 5. A sustainable business model for the long-term maintenance and operation of the system. VI. Timeline: The project is estimated to be completed within 18-24 months, including drone development, testing, and refinement. VII. Conclusion: The solar-powered drone-based weed cutter system, combined with GSI data, represents an innovative and environmentally friendly solution for lake weed management. By funding this project, we can make significant strides in improving the health and sustainability of our lakes while reducing the reliance on harmful chemicals and manual labour. We seek your support to bring this transformative technology to fruition. This project aims to address the persistent issue of aquatic weed control in lakes and other water bodies using an innovative and environmentally friendly approach. By combining drone technology with GIS, we can develop a system that not only cuts weed efficiently but also provides valuable insights for lake management and conservation. This project has the potential to significantly improve the health and usability of our lakes while reducing the environmental impact of weed control methods. Signature Date: 15/09/2023 Sd: PI: Dr Ashfauq Farooq Aga Assistant Prof cum Scientist Aquaculture Engineering Division of Fishery Engineering Faculty of Fisheries Engineering, Rangil, Ganderbal Shere-Kashmir University of Sciences and Technology- Kashmir