Enhancing Crop Yield Through IoT- Based Precision Agriculture: An Optimized Multi-Parameter System for Solar-Powered Tunnel Farming
Agriculture is crucial for the economic development of our nation. As the human population continues to expand, we must take specific measures to meet future food demands. Soil remains the essential foundation for plant growth. Manual soil nutrient measurement methods are time-consuming, leading farmers to skip lab testing. This results in continuous cultivation of the same crop, depleting soil fertility. This paper delves into the execution of automation of tunnel farming & green house. Crop yield largely depends on soil fertility and moisture levels. Fertilizer recommendations are typically made based on the nutrients available in the soil. A system has been proposed to implement precision agriculture using Soil Integrated (NPK 7 in 1) sensor which measures Nitrogen, Phosphorus, Potassium, Electrical Conductivity, PH, Humidity and Temperature, Soil Moisture Sensor and Humidity & Temperature sensor for measuring of internal Temperature of control environment and the complete system is IoT based so sensor detects the parameters if there is deficiency of Nitrogen, Phosphorus and Potassium than controller gives instructions to pumps to operate and provides the respective fertilizer to soil so crop deficiency fulfilled. In case of low humidity in surrounding than motors start operating and control shed has been opened to maintain the humidity level. IoT enabled Smart farming enables growers and farmers to enhance productivity while minimizing resource wastage, including the judicious use of fertilizers to prevent environmental pollution caused by excessive usage. All real time parameters are visible on the digital display on a user-friendly interface designed for growers and farmers to easily interpret, helping them determine the optimal conditions for their plants.
Authors
- Haseeb Ahmed (ORCID: https://orcid.org/0000-0001-8645-2718)
- Ali Raza (ORCID: https://orcid.org/0000-0001-5429-9835)
- Muhammad Aqeel Ashraf (ORCID: https://orcid.org/0000-0003-3151-3397)
- Shahid Atiq (ORCID: https://orcid.org/0000-0002-9774-2291)
- Abubakar Siddique (ORCID: https://orcid.org/0000-0002-3253-802X)
- Zeeshan Aslam
Institutions
- Khwaja Fareed University of Engineering and Information Technology (PK)
Publication Details
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1109/etecte63967.2024.10823752
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.60