Smart System for the Tornado Prediction and Protection
Tornadoes are among the most destructive natural disasters, typically forming in areas with significant air pressure differences between the surface and the atmosphere. While it's not feasible to stop these storms, new technologies offer ways to reduce their impact. One innovative strategy involves setting up a protective infrastructure outside populated zones, roughly 150 meters away, to mitigate tornado damage. This system features a perimeter of pole-like structures outfitted with sensors and Raspberry Pi modules for control. Each pole includes a telephoto lens with a 128-megapixel camera for long-distance image capture, along with infrared and proximity sensors. These are paired with TINY ML and EDGE IMPULSE modules to apply machine learning to the sensor data. Keras and CNN models process the images to identify approaching tornadoes. Additionally, high-speed wind turbines are positioned around the perimeter. These turbines generate cold winds to create a protective barrier, equipped with large turbines and cooling elements managed by Raspberry Pi modules. This setup aims to deflect and lessen the tornado's impact. A power grid connection breaker, controlled by a microcontroller, automatically disconnects power within the protected area upon tornado detection to reduce potential damage. The sensors on the poles are linked to a central control unit, which communicates with a centralized system through Bluetooth 5.0 and Wi-Fi modules. This enables data to be sent to a cloud server and alerts to be issued to residents via an integrated alarm system. Early warnings are crucial for ensuring safety and reducing fatalities. To prevent panic and protect property, the infrastructure includes safety systems that connect to each household. Raspberry Pi modules in homes can detect gas leaks and monitor electrical systems. The sensors in the perimeter also check for hazards like broken wires or gas leaks, sending alerts to residents. This proactive approach enhances safety and minimizes property damage.
Authors
- Vikas Wasson (ORCID: https://orcid.org/0000-0003-2334-9144)
- Devyansh Batra
Institutions
- Chandigarh University (IN)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/icicnis64247.2024.10823368
- Citations
- 1
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.28