Tenglong Ren
Papers
2
Total Citations
14
H-Index
2
About
Tenglong Ren is a researcher at the forefront of smart agriculture, specializing in the integration of the Internet of Things (IoT) and robotics for precision irrigation. His work directly addresses critical inefficiencies in traditional farming, such as poor mobility, imprecision, and lack of adaptive feedback. Ren’s major contributions include the design and implementation of novel IoT irrigation systems enhanced by intelligent path planning algorithms. His most cited paper (2021, 9 citations) introduces a system that couples IoT sensors with a precision irrigation robot, overcoming low adaptability and feedback issues. A subsequent work (2020, 5 citations) further refines this concept by developing a cost-effective, mobile robot capable of autonomous navigation and targeted water delivery. These innovations demonstrate a clear trajectory toward scalable, automated solutions for sustainable agriculture. Ren’s research is notable for its practical, implementation-focused approach, bridging the gap between theoretical algorithms and real-world agricultural challenges. His work is a valuable resource for students and researchers exploring the convergence of robotics, IoT, and environmental stewardship.
Research Focus
Key Achievements
Top Papers
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- 2