Leveraging The Power Of IoT, AI, And ML For Smarter Disaster Management

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Leveraging The Power Of IoT, AI, And ML For
Smarter Disaster Management
In todays world, the integration of the Internet
of Things (IoT) with Artificial Intelligence (AI)
and Machine Learning (ML) is revolutionizing
various sectors, including disaster management.
These technologies can process large volumes of
data in real-time, forecast potential risks,
and deliver early alerts, which
significantly helps in preventing loss of life
and minimizing damage.
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For instance, AI and ML models can monitor
environmental conditions, detect anomalies, and
alert authorities to impending natural disasters,
enabling timely evacuations and preparedness.
However, as seen in the devastating Wayanad
landslide, natures fury can still take a toll
despite technological advancements. On July 30,
2024, Wayanad in Kerala, India, faced devastating
landslides due to continuous rainfall. The
affected areas witnessed fatalities, injuries,
and mass displacement of people, and the disaster
caused substantial property damage. Despite the
tragedy, the deployment of AI and ML by
organizations like the Indian Meteorological
Department (IMD) and ISRO played a crucial role
in issuing early warnings and guiding rescue
operations, mitigating what could have been a
more significant loss. The Geological Survey of
India highlights that nearly 50 of Keralas area
is prone to landslides, emphasizing the
increasing risks of climate-related disasters and
how AI/ML integration can help tackle such
disasters in the future. This recent event has
highlighted the essential role that Artificial
Intelligence (AI) and Machine Learning (ML) play
in managing disasters. Understanding The
Causes Keralas hilly regions, with slopes
exceeding 20 degrees, were hit hard by the
Wayanad landslide, primarily due to over 570 mm
of monsoon rainfall in 48 hours. This intense
downpour saturated the soil, causing hillsides to
collapse and triggering destructive mud and
debris flows. Deforestation and haphazard
construction have worsened the problem. On
August 1, ISROs National Remote Sensing Centre
released satellite images showing 86,000 square
meters of land sliding at Chooralmala, revealing
that heavy rainfall triggered this catastrophic
event, widening the nearby Iruvanjippuzha River.
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AI ML Aiding Early Warning Systems In the days
before the landslide, AI and ML technologies were
key in predicting the risk. AI and ML systems,
integrated by IMD and ISRO, played a pivotal role
in predicting these landslides. These systems
analyzed real-time data from IoT sensors,
satellite imagery, and weather models, providing
timely alerts to local authorities. This
proactive approach prompted the evacuation of
residents in some areas to relief camps starting
on July 29. Advanced algorithms analyzed data
from satellite imagery, weather forecasts, and
soil stability, enabling early warnings that
saved lives. ISROs AI-powered Landslide
Monitoring and Prediction System (LMPS) used
machine learning to analyze real-time data from
sensors across the region. It successfully
identified high-risk areas and issued alerts,
enabling timely evacuations before the landslide
occurred. A crowdsourced effort led to the
development of Satark, a meteorology-based
landslide prediction model for Indias Western
Ghats. This system, created by community
scientists with expert assistance, predicts
landslides along Indias southwestern coast with
76.5 accuracy, a day in advance. Post-Tragedy
Support Through AI ML After predicting the
Wayanad landslide, AI and ML were crucial in
guiding rescue and relief efforts. AI-powered
drones surveyed the affected areas, helping
locate survivors. Additionally, AI-driven
analytics optimized resource distribution,
ensuring aid reached the most vulnerable. Machine
learning models also assessed long-term impacts,
providing insights for future disaster planning.
On August 9, a mysterious underground noise
caused panic in several Wayanad villages. The
India Meteorological Department later confirmed
seismic activity in parts of Wayanad and
Kozhikode.
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Enhancements In AI ML Integration On July 29,
the Hume Centre for Ecology and Wildlife Biology
in Kalpetta, Wayanad, notified authorities of a
possible landslide in Mundakkai, giving them a
15-hour prior warning. Their accurate prediction
was based on micro-level weather data from 200
rain gauges across the district. Since 2018,
theyve mapped landslides and created a landslide
occurrence susceptibility map using GIS
techniques. This map considers factors like soil
type and land fragmentation. To enhance AIs
effectiveness, integrating it with local
knowledge, expanding sensor networks, and
refining machine learning models are
crucial. Averting Future Tragedies To prevent
future tragedies like the Wayanad landslide, it
is imperative to invest in AI and ML
technologies. Governments and local authorities
must prioritize the development of early warning
systems and ensure that these technologies are
accessible to all. Public awareness campaigns
about the role of AI in disaster management can
also play a vital role in building trust
and encouraging community participation. How
EnFuse Solutions Can Contribute EnFuse Solutions
India can play a pivotal role in advancing AI
ML technologies by annotating and labeling data
to train models with precision. By leveraging our
expertise in AI, we can develop more
sophisticated predictive models that consider a
wider range of variables, ensuring more accuracy.
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Our commitment to AI and ML advancements is
driven by the belief that technology can save
lives. By integrating cutting-edge AI and ML
solutions into systems, EnFuse Solutions India
aims to create a safer, more resilient
world. Conclusion In the end, these harsh
tragedies served as a stark reminder of natures
violent force. However, it also highlighted the
potential of AI and ML in disaster prediction,
management, and recovery. With continuous
advancements and strategic integration, these
technologies can play a crucial role in averting
such tragedies in the future. EnFuse Solutions
is committed to driving these innovations
forward, ensuring that the lessons learned from
such disasters translate into safer communities
across the globe. To make a meaningful and
lasting impact by saving lives using AI/ML, data
tagging, and annotation, consider partnering with
experts like EnFuse Solutions India. Read More
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