Integrated internet of things (IoT) solutions for early fire detection in smart agriculture - Abdennabi Morchid; Zahra Oughannou; Rachid El Alami; Hassan Qjidaa; Mohammed Ouazzani Jamil; Haris M. Khalid (Results in Engineering)
The integration of internet-of-things (IoT) technologies is proving crucial for optimizing crop management and monitoring in smart farming. The challenges posed by climate change which involve 1) increased pressure on natural resources, and 2) heightened food safety requirements, eventually call for innovative solutions to protect agricultural resources. Early fire detection, in particular, is essential to prevent major damage and ensure the sustainability of agricultural practices. This article presents an advanced IoT architecture for early fire detection. The proposed architecture integrates 1) smoke and flame sensors, 2) a Raspberry Pi for local processing, and 3) the ThingSpeak platform for data storage and visualization. The system is based on a three-layered architecture: 1) the IoT device layer, 2) the cloud layer, and 3) the application layer, enabling real-time collection and analysis of environmental data. Sensors collect real-time environmental data, which is then transmitted to ThingSpeak for storage. The ThingSpeak platform, combined with MATLAB visualization tools, enables continuous monitoring and in-depth trend analysis of historical data. The results show a clear improvement in accuracy and responsiveness in fire detection while contributing to the safety of agricultural resources and more sustainable management. The blend of IoT technologies, real-time data processing, and cloud-based visualization in this proposed detection system represents an important step towards safer and more resilient agriculture in the face of environmental risks.