Table 2 Summary of related work using emerging technologies for agricultural pest and disease detection.
From: AI and IoT-powered edge device optimized for crop pest and disease detection
Technology | Strengths | Limitations |
|---|---|---|
Real-time monitoring and control, low-cost and energy-efficient sensor deployment, continuous data collection, High efficiency, and sensor network | Limited battery life for remote deployment, sensor calibration complexity, limited connectivity in rural areas, and security problems | |
High resolution aerial imaging, large and inaccessible farmland coverage, and rapid data acquisition | susceptibility to weather condition, limited flight period, complex design, and data processing overhead | |
Traceability, security, decentralized data acquisition and decision-making, and reliable supply chain | High computational resource demand, complexity for small-scale systems, not yet widely adopted for smallholder farmers | |
extremely low latency, fast data transmission for real-time analytics, and suitability for cloud computing | Limited coverage in rural/remote farming areas, advanced infrastructure requirements | |
High detection and prediction accuracy, feature extraction from complex agriculturally based data, human like text generation for farmers | Requires large datasets, high computational cost, and black-box decision-making process, making difficult for farmers to interpret | |
Integrated smart farming with real-time imaging and edge intelligence, intelligent decision support to farmers, and precision interventions (e.g., targeted spraying) | System complexity, synchronization and interoperability challenges, energy consumption constraints, and require strong internet connectivity which may be limited for rural and remote farmlands |
