Advancements in remote environmental monitoring are to play important roles in predicting natural disasters and protecting communities. One innovative approach is the use of Green Internet of Things (IoT) technology clubbed with fog analytics. The project mainly focuses on ensuring reliable connectivity for IoT devices everywhere. This means the connectivity should be ensured even in remote and challenging locations. All these will help early warning systems for natural disasters such as landslides. As an aftermath, authorities can respond quickly and effectively to potential threats.
The project is being funded by Amrita Vishwa Vidyapeetham in collaboration with the Ministry of Earth Sciences (MoES), the Department of Science & Technology (DST) and the European Union. One example is an IoT-based landslide monitoring system that is equipped with several sensors such as rain gauges, pore pressure sensors, movement detectors and inclinometers. All the sensors are powered by solar energy.
Meanwhile, ensuring reliable communication in remote areas and within large-scale IoT deployments presents some challenges. The monitored area is typically a hilly region with diverse geographic characteristics. This makes network connectivity a hurdle. Real-time streaming of sensor data requires overcoming issues like asymmetric links, changing network conditions due to rough weather, limited solar power and network fail-over or reconnection problems. This is crucial for transmitting data back to a Data Management Center located 2,500 kilometers away.
The IoT gateway is equipped with heterogeneous wireless networks and employs advanced technologies such as fog analytics and reinforcement learning algorithms to manage network connectivity effectively. Three types of bandit algorithms are used and these are approximate, contextual and adversarial. These help in selecting the most efficient network dynamically.
