Smart Cities and Quality of Life: Internet of things can prepare cities intelligently against natural disasters

January 18, 2018

More people live in cities today than at any time in human history, and the urbanization of the global population appears set to continue as the 21st century unfolds. The multi-faceted pressures of urbanization will force cities to develop efficiencies and strategies in order to remain viable. Smarter ways of doing everything better, with fewer resources, will be required. So will the ability to forecast disruptive events such as natural disasters and their effect on urban dwellers and the infrastructure that supports them.

Internet of things can prepare cities against natural disasters

Government agencies should consider leveraging the internet of things (IoT) and other web-driven technologies to obtain timely and accurate data that can better inform decisions and actions. Using the most current technology could help them more efficiently and safely address these costly disasters. However, this type of progress will require more than just employing the IoT to improve emergency preparedness and response; response teams have to be ready to receive, interpret, and take action on the data.

Gathering Data Before a Disaster Strikes

Today, disaster responders gain reliable, timely information only when they reach an emergency zone and take stock of the situation. In the case of hurricanes and major weather events, physical and technical roadblocks often prevent response teams from obtaining critical data to track damages, prioritize response needs, and keep the public informed so that people know how to stay safe. Ineffective communication channels, overburdened response systems, satellite disruptions, and internet blackouts further impede people from getting the help they need.

That is where the value of IoT sensors that collect data and systematically broadcast signals from emergency areas comes into play. These sensors can relay information about their surroundings directly to government agencies and emergency teams. For example, sensors can measure temperature, water quality, pressure, level, smoke, and humidity, to name just a few uses. In the case of wildfires, sensors can detect how far and how fast is the fire spreading. For hurricanes or tsunamis, sensors can monitor water levels to send alerts at the first sign of flooding. Sensors can also be used to detect the presence of harmful gases or chemicals emanating from a storage tank, factory, or plant in the path of destruction. These devices can be critical for urgent decisions like whether to evacuate an area at risk of flooding, or how to guide residents to the safest exit routes ahead of an emergency.

Connecting People and Information During a Disaster

In order to respond with precision, government agencies and emergency response teams should establish communication systems between the mobile devices of an at-risk area’s residents and IoT sensors in the field. Doing so can help facilitate and expedite a local response during the disaster. The system should respond to incoming information based on data it receives from the IoT sensors and signals from citizens’ mobile devices. For example, if a citizen messages a public emergency text line to ask where to go to avoid local flooding, the system could provide a recommendation based on water level data it receives from deployed sensors. An data-backed automated response can ensure information reaches the people who need it most. This data should be collected centrally, monitored regularly by response officials, and proactively used to inform automated alerts that are broadcast to citizens’ mobile devices within a certain radius of the hazard area.

Response teams can also use the sensor data for coordination, analytics, outreach strategies, and on-the-ground tactics. These actions will vary from case by case. In the case of a food stamp program, government officials could use the information to decide (1) how and when to reach out to the affected population, (2) where to set up temporary benefit distribution centers, because the primary centers (supermarkets, convenience stores, and so on) may not be functional, and (3) how to ensure benefits are distributed correctly.

Predicting Natural Disasters & Early Warning Systems

As cities become smarter, natural disasters will become more predictable. By monitoring big data and forecasting future events, cities will be able to significantly counteract the impact of natural disasters through heeding early warning signs and planning evacuations.

One example of an early warning system is the network in use at Popocateptl, the most active Volcano in North America. If Popocateptl did erupt, it would affect local Mexican villages near the Volcano. In an effort to prevent this disaster, the Mexican government has set up a data collection network that gives the villages early warnings of any spike in seismic activity.

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