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Decision Support

Predict

Disaster and Emergency Prediction & Impact Model

A fairer and more personalised credit decision
For:
Payment and credit providers
Goal:
Improved Customer Experience
Moving Beyond Generalised Linear Models: A sophisticated pricing strategy incorporating competitor pricing
For:
Customer pricing Actuaries
Goal:
Increase Revenues
Machine-learning based triage to determine low-severity patients that can be fast-tracked to admission in ED due to their short discharge length
For:
Emergency Departments in hospitals.
Goal:
Improved Employee Efficiency
Disaster and Emergency Prediction & Impact Model
For:
National-level disaster management professionals, Climate change adaptation experts, Government agencies, At-risk communities
Automated threat enrichment intelligence in Cyber security
Goal:
Improve Operation Efficiency
Deep reinforcement learning for personalized treatment recommendation
For:
Clinicians who prescribe long-term and adjustable treatments
Goal:
Improved Employee Efficiency
Applying machine learning to predict patient risk for in-hospital new infections
For:
Hospitals
Goal:
Improved Customer Experience, Anticipate Risks
Large Companies
Small Companies
Management - Market Intelligence
For:
Product managers and Marketers.
Scope:
Growing active users for a music streaming service by identifying high-value customer behavior.
Goal:
Improved Customer Experience, Increase Revenues
Weather Forecasting in Agriculture
For:
Farmers
Goal:
Anticipate Risks, Improve Operation Efficiency
AI for customers' loss prevention of telecommunication services
For:
Telecommunication companies
Goal:
Improved Customer Experience
Large Companies
Manufacturing and Factories – Predictive Maintenance
For:
Operation, R&D
Scope:
Avoiding unplanned shutdowns in Manufacturing using Machine Learning to predict failure states in equipment.
Goal:
Anticipate Risks, Improve Operation Efficiency
Disaster and Emergency Prediction & Impact Model
For:
National-level disaster management professionals, Climate change adaptation experts, Government agencies, At-risk communities.

Disaster and Emergency Prediction & Impact Model

For:
National-level disaster management professionals, Climate change adaptation experts, Government agencies, At-risk communities
Problem addressed
Whenever a natural disaster like a flood or a heat wave occurs, warnings and other risk-related information might be imprecise or out of date. Most of the risk-related information currently floats on a macro-level, covering hundreds of square meters, and is too complex for at-risk people to comprehend.
It was necessary to localize the risk data to a neighborhood level to support the development of long-term resilience in the communities that are most at risk. Their extensive experience reacting to many emergencies and disasters on the ground must be automated, scaled, and coded using a solution.
Description
A cutting-edge model blending AI and machine learning capabilities is developed to plan and react to disasters more successfully. This model forecasts hyper-local risk information for early warnings and intervention using historical data and satellite photos. 
The basic tenet of the approach is that a house's roofing can serve as a stand-in for its socioeconomic status. Therefore, the adapting and recovering capacities of a family residing in a sizable concrete home and a family living in a temporary metal sheet home would be different. 
The effects of the destruction brought on by a disaster are noticeably different for each of these dwellings when two of them are present in the same region. The backbone of this AI system is the mapping of this roof material data on satellite imagery and other spatial factors.
The solution generates hyper-localized risk data that can be used by various stakeholders in disaster response. These stakeholders include experts in climate change adaptation, government agencies, and communities at risk on a national scale. It provides people with precise instructions on how to protect their homes, pets, livelihood, and possessions.
The solution's scalability is another plus. It can respond to a variety of disasters, including earthquakes, heat waves, and floods.
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Image
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Machine Learning
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Predict / Forecast
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