The Role of AI and IoT in Disaster-Risk Reduction
In an era defined by technological innovation, the convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) has the potential to augment information flows to generate effective real-time feedback. The access to edge computing and sensors (stretching from hyperspectral satellites to nano probes) have become radically democratized, enabling new use cases for these technologies to be applied, specifically in disaster-mitigation situations.
Sitting between sprawling power grids, volatile oil and gas installations, and smart cities, there are no shortage of situations where field workers are faced with missing information and risky, but important, decisions.
- Does a firefighter break down a door while risking the creation of a secondary explosion?
- Does a tower climber complete the job before a storm, or must he descend immediately?
- Does a police officer need to evacuate a chemical explosion or can he continue pulling others out of the hazardous site for another 10 minutes?
These decisions no longer need to be based in human-intuition . Data can be collected from multiple sources and fed into robust models to deliver real-time feedback on a situation, to field agents.
With the effects of climate change becoming increasingly volatile, the surface areas where these technologies can iterate on human workflows is growing. Let’s dive deeper into a few examples.
Case Study 1: Smart Agriculture
On local smart farms in southern Somalia, IoT sensors are deployed to monitor soil moisture, temperature, and crop health. With the help of sensors from MaxBotic, an AI-agent continuously processes this data and cross-references it with weather forecasts. When a sudden and unexpected heatwave approaches, the AI-agent alerts field workers in real-time, recommending an immediate shift in irrigation schedules and the deployment of sunshades to protect the crops. This proactive intervention helped prevent crop damage and ensured a more bountiful harvest.
See: Internet of things based agricultural drought detection system: case study Southern Somalia
Case Study 2: Construction Site Safety
On a bustling construction site, IoT sensors are embedded in heavy machinery and workers’ safety gear. An AI agent analyzes the real-time data, looking for potential safety hazards. When a crane’s stability begins to fluctuate due to strong winds, the AI agent alerts the crane operator and site supervisor, recommending an immediate halt to operations involving tall structures. This timely intervention prevents a potential disaster and safeguards the lives of workers on-site.
Case Study 3: Traffic Management in Smart Cities
In a smart city equipped with IoT-connected traffic infrastructure, an AI agent monitors traffic flow, road conditions, and real-time data from vehicles. During rush hour, a sudden accident occurs, blocking a major artery. The AI agent swiftly reroutes traffic and communicates alternate routes to commuters through connected vehicles and roadside displays. This dynamic traffic management minimizes congestion, reduces travel times, and enhances overall safety on the city’s roadways.
See Intelligent Traffic Monitoring, Prioritizing and Controlling Model based on GPS
These case studies highlight how AI agents, in tandem with IoT sensors, empower field workers with real-time information and recommendations, enabling them to make more informed decisions and respond promptly to changing conditions, ultimately enhancing safety and efficiency in various industries.
The fusion of IoT and AI is a potent force poised to revolutionize disaster-risk reduction and safety across a spectrum of high-risk scenarios. These technologies are expanding their reach, aiding real-time decision-making in our ever-changing climate. The case studies we’ve examined affirm technology’s potential to improve safety, productivity, and resilience. To sustain success, ongoing innovation, collaboration, and adaptation are crucial. Our imperative is to nurture and harness this alliance for society’s benefit, making disaster-risk reduction a reality.
— Satvik Agnihotri
