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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62502
Volume:
10 |
5 |
May 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Electrical Engineering
V.P.M.'s College of Engineering, Thane
This paper presents the design and implementation of Agri-Bot, an autonomous multifunctional agricultural robot aimed at addressing key challenges in modern farming. Agri-Bot integrates IoT technology with robotic systems to perform essential tasks such as seed sowing, soil moisture monitoring, pesticide/water spraying, and grass cutting. The robot utilizes Node MCU for real-time data processing and remote control via a mobile application (Blynk), enabling precision agriculture. Field tests demonstrated a 50% reduction in seed sowing time, efficient resource management, and improved labor productivity. The system’s modular design, cost-effectiveness, and sustainability features make it a viable solution for small-scale farmers. This work contributes to the growing field of agricultural robotics by offering a scalable, data-driven approach to automate labor intensive tasks.
KEYWORDS
The anticipated outcomes of implementing this multifunctional agricultural robot include: Increased Efficiency: By automating labor-intensive tasks, the robot enhances the speed and accuracy of agricultural operations, leading to higher productivity levels. Labor Reduction: Automation reduces the reliance on manual labor, addressing labor shortages and freeing up farmers to focus on strategic decision-making. Cost Savings: The robot offers a cost-effective solution for farmers by minimizing the need for expensive machinery and labor, ultimately improving profit margins. Sustainability: The use of renewable energy sources (such as solar power) and battery systems contributes to environmentally friendly farming practices, reducing the carbon footprint associated with traditional agricultural methods. Data-Driven Farming: The integration of IoT technology allows farmers to make informed decisions based on real-time data, improving resource allocation and management
1. Nitin P V, Shivaprakash S. "Multi-purpose agricultural robot." International Journal of Engineering Research, 20 May 2016. 2. Abdul Rahman et al. "Seed sowing robot." International Journal of Computer Science Trends and Technology (IJCST), Mar-Apr 2017. 3. Jha, R., & Prasad, A. "Advancements in Agricultural Robotics." International Journal of Agriculture and Crop Sciences, 2018. 4. Kumar, V. et al. "Robotics in Agriculture: A Review." Journal of Agricultural Engineering, 2019. 5. Patel, N. et al. "IoT-Based Smart Farming Systems." International Journal of Advanced Research in Computer Science, 2020. 6. Blynk Documentation. "Getting Started with Blynk." Available: Blynk Official Site. 7. Texas Instruments. "Motor Driver IC L293D Datasheet." Available: TI Official Site. 8. Arduino Documentation. "Arduino UNO Specifications." Available: Arduino Official Site. 9. MG995 Servo Motor Datasheet. Available: TowerPro Official Site. 10. Node MCU Documentation. "Node MCU ESP8266 Specifications." Available: Node MCU Official Site.
Publication Date
5/5/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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