Celestine Iwendi

Central South University of Forestry and Technology, University of Greater Manchester

Papers

Total Citations

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About

Celestine Iwendi is a multidisciplinary researcher whose work spans robotics, control systems, artificial intelligence, and edge computing applications in agriculture. His influential 2019 study on two-wheeled self-balancing robots demonstrated a sophisticated Proportional-Derivative Proportional-Integral (PD-PI) control framework implemented on a 32-bit microcontroller, advancing the field of autonomous mobile robotics and robust navigational control in sensed environments — work that has garnered 66 citations and established him as a credible voice in intelligent robotic systems. More recently, Iwendi has extended his expertise into precision agriculture and deep learning, developing the PFDI model — a Faster-CNN-based system designed to accurately identify diseases in citrus fruits within edge computing environments. This work addresses critical food security challenges by leveraging context data fusion and machine learning to protect high-value crops. With research touching robotics autonomy, embedded systems, computer vision, and smart agriculture, Iwendi exemplifies the kind of cross-domain innovation increasingly valued in modern engineering research. His growing citation record reflects a trajectory of meaningful, applied contributions that bridge theoretical computation with real-world problem-solving across diverse technological domains.