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Researchers Using The IoT To Predict Natural Disasters

By Michael Luciano | August 1, 2018

From 2005-2015, 242 natural disasters occurred in the United States alone. These figures only represent a small fraction on how many of these events affect people around the world during (and since) this timeframe. While catastrophes like hurricanes, tornadoes, earthquakes, and tsunamis are beyond humanity’s control, researchers are have been attempting to mitigate the destruction from these storms and geologic processes using the Internet of Things (IoT) technology.

We’re in the midst of an era where scientists and experts are beginning to utilize smart technologies for mitigating and preventing loss of life and property caused by severe weather and geologic occurrences. Although most coverage on natural disasters focuses on the actual event and its aftermath, innovative companies around the world are developing technologies to help communities, governments, and researchers better prepare. Whether it’s for supplies or certain kind of catastrophe, proper preparation for extreme incidents focuses on forming a disaster recovery plan aimed at reducing hazards for people and property, along with facilitating rescue and recovery operations.

Technologies being developed are making it possible to become aware and anticipate the potential risks before, during, and after a natural disaster. LoRa Devices, for example, combines low-power wide-area network sensors, wireless technology, and sophisticated algorithms in this particular focus of study. Using long-range, low-power wireless chipsets for uses in all IoT application types, LoRa operates end-to-end AES128 encryption, geolocation (without GPS), and relay of data through LoRaWAN networks.

The technology is used in sensors and end nodes for IoT applications to collect and relay data, along with communicating bi-directionally through the LoRaWAN protocol. Their sensors and meters have already helped experts make more accurate predictions on cataclysms like earthquakes and volcanic eruptions. This is one of many examples from the swath of IoT devices and systems, where researchers are applying devices and networks to mitigate impacts of future catastrophes by implementing early warning systems.

Predicting these events entails more than analyzing weather patterns, with effective methods involving the identification of hazard areas and potential triage zones on maps. These techniques also involve using communication platforms without relying on cellular networks or landlines. Information like patient data and medical records are even accounted for to ensure proper care should a disaster strike.

Naturally, there are limitations on the ability to predict natural disasters. Factors like network infrastructure, connectivity issues, financial constraints, and shortcomings in communication methods are among some of the major hurdles researchers have yet to properly fix. While communication is often disregarded as being a limitation in this particular area, many natural disasters occur in undeveloped parts of the world, where network deployments are nonexistent or still in various stages of development. Even in the U.S., lapses in network connectivity transmitting data from weather reference points can keep early warning alarms from being issued. These scenarios further emphasize why effective communication of risks and expressing an event’s severity can make a difference in saving lives. Something like an efficient low-cost IoT network can ensure communications remain online.

Technologies like sensors with greater sensitivity and data capabilities, along with deploying them quickly and cost-effectively can help with forecasting natural disasters. Forming IoT networks of weather base stations in the Caribbean, for example, can become an early warning system for storms like hurricanes and tropical depressions. Evidently, the ability to analyze years of historical data on weather patterns and previous natural disasters can aid in identifying timing and severity of weather events, along with mobilizing local authorities. The LoRa tag, for example, which is equipped with a printed battery designed for integrating into products or systems that send messages to the cloud when an event is detected, can tap into the significant advances in abilities of the IoT for natural disaster preparedness and prediction. The tag is expected to enable increases of completely new IoT application types, requiring real-time, reliable feedback including logistics and shipping, healthcare and pharmaceutical, asset tracking, and general-purpose compliance applications.

Looking forward, experts are continuing to formulate ways of combining IoT and artificial intelligence (AI) in an ongoing effort to reduce and manage conditions of hazard exposure and vulnerability, preventing further loss of life and property.

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Filed Under: M2M (machine to machine)

 

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