The United Nations’ Asia-Pacific social agency recently highlighted in a report the potential role of technological innovations in mitigating the impact of natural disasters in the Asia-Pacific region. According to this report, since the 1970s, two million people have died due to natural calamities in the region, accounting for 59% of the global death toll. The gravitas of the situation is further intensified with the rising global temperatures and climate change leading to frequent and intense floods, cyclones and droughts. More alarming is the significant damage caused by these disasters in Asia and Pacific countries, measuring as a percentage of GDP, is far greater than other global regions. The gap sadly continues to widen.
Big Data to the Rescue
In a bid to counter this grave scenario, the application of big data has emerged as a promising solution. Big data can compile inputs from diverse sources like satellite imagery, drone videos, simulations, crowdsourcing, social media and global positioning systems. This conglomerate of information can help identify and locate those most at risk, provide an early warning system ahead of a disaster and carry out targeted relief operations post the catastrophe.
Application of Big Data in Disaster Risk Reduction
The four integral components of disaster management include prevention, preparedness, response and recovery. Each phase can be significantly improved using a big data-driven sensor network. Swift actions performed based on accurate predictions can lead to substantial reductions in mortalities and economic losses. Let’s delve deeper into how big data can revolutionize each phase.
Flood and Cyclone Forecasting
Modern technologies like computer simulations and machine learning can aid in predicting the location and severity of floods. These predictions are accurate and hence more reliable.
Efficient Earthquake Early-Warning Systems
By leveraging sensor webs and the Internet of Things (IoT), we can develop efficient earthquake early-warning systems. These systems can alert residents in the vicinity and provide enough time for evacuation and prevent massive loss of life.
Quick Damage and Impact Assessment
Remote sensing via satellites and drones allow for rapid assessment of damage and people affected. With this data, it is easier to prioritize disaster responses and provide help where needed the most.
Public Data for Targeted Benefits
Public data like India’s digital ID system (Aadhaar) can be used to offer targeted benefits to millions of small and marginal farmers who are severely affected by droughts.
| Disaster Type | Impact | Big Data Intervention |
|---|---|---|
| Floods and Cyclones | High risk of life and property | Predictive computer simulations and machine learning |
| Earthquakes | Magnitude and timely alerts | Sensor webs and IoT |
| Drought | Agricultural distress | Public data for assistance |
Understanding Big Data
At its core, ‘Big Data’ characterizes datasets that are too large to be stored and analyzed using traditional methods. The notable characteristics of big data, often referred to as the three Vs- Volume, Velocity and Variety distinguish it from other forms of data. It’s worth noting that the advent of Big Data has been primarily due to the decreasing costs of sensory and mass digitization of systems and processes worldwide.