Natural disasters such as hurricanes, tornadoes, and floods have devastating effects on communities across our country. 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. However, 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. They should start by deploying IoT sensors on critical infrastructure in order to gather data before a disaster. This data can be combined with demographic data to inform plans about which citizens will need what kinds of assistance once a disaster strikes. During the disaster, real-time data from sensors can help agencies send current information to response teams and citizens as the situation changes.
When a disaster strikes, federal, state, and local governments need a coordinated strategy, accessible data, and a skilled workforce to manage the response. Natural disasters such as hurricanes, tornadoes, and floods have devastating effects on communities across our country. Since 1980 the U.S. has sustained more than 200 weather and climate disasters, with cumulative costs exceeding $1.1 trillion.
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’s 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.
In practice, this starts with establishing systems that connect local data to government responders. Technical teams could deploy sensors that send web-linked data to a digital command center that government officials can access remotely while at the scene. Drones could surveil disaster areas during the search-and-rescue phase and then move to data collection to support the recovery effort once the immediate danger has passed.
In order to optimize effectiveness, agencies should place web-linked sensors on physical assets such as levees, bridges, and utility poles to monitor risk factors such as rising water levels in low-lying areas and to alert authorities when there’s an issue with critical infrastructure. In areas vulnerable to flooding, for example, response teams should arrange sensors in various locations so that one device going down won’t take down the entire network. Establishing a stream of data from sensors in at-risk areas can also help pinpoint and prioritize which neighborhoods need to be reached first.
Response teams can gain an even clearer picture of the emergency situation if the sensor data is combined with Census-verified demographic and relevant third-party data. Increased socioeconomic and demographic data would be useful to informing outreach tactics, for example in a community where people speak many different languages. Analytics-backed information would enable local, state, and national teams to geotarget messaging to neighborhoods at most risk – a neighborhood with high concentrations of elderly populations who might not have access to transportation, for example.
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.
Emergency response organizations must also know which communication channels work best to reach the affected citizens. For instance, if the at-risk population is predominantly Spanish-speaking, then preparedness messaging should be done in Spanish. When dealing with an elderly population, the outreach can be done through television, newspapers, and radio rather than tech-driven channels like text alerts and apps. This targeted communication is a shift from the conventional “one size fits all” approach. Agencies will need both a thorough change management process to describe the benefits and efficacy of the IoT-based approach and appropriate training in how to adopt it.
We’re seeing the early stages of IoT-based response happen already with the Department of Homeland Security’s Consolidated Asset Portfolio and Sustainability Information System (CAPSIS) system. Responders to the hurricanes in Texas and Puerto Rico and the wildfires in California used field data streaming to CAPSIS at DHS headquarters to take stock of the damage. At the state-level, Wyoming’s Department of Transportation has rolled out a pilot program to use vehicle-to-vehicle, vehicle-to-infrastructure, and infrastructure-to-vehicle connectivity to improve monitoring and reporting of road conditions to drivers along I-80.
Timing is everything in a disaster situation. By incorporating IoT data into emergency response plans, public sector agencies and responders can use real-time information to make plans and reach the citizens who need help.
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