An AI solution that helps those struggling with housing issues and homelessness


The service manager for housing and homelessness in a large Canadian City finds itself unable to adequately respond with appropriate housing and resources to address the growing needs of its population.

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Objectives

We were tasked with developing a novel data, continuous learning, digital platform to proactively leverage real-time data for temporary housing requests. Our goal was an AI deployment that would provide asset management of city assets, root cause analysis of client needs and situational awareness at the city and sub-population level.

Applied Intelligence

Through our AI Enterprise Server (AIES), we incorporated Machine-learning techniques - pattern recognition Machine-learning, deep learning, image processing, language and speech recognition techniques to detect approximate classes, clusters or outliers.

Our initial focus was on automating data curation and integration, including social housing, public health, shelter, youth, police, demographics, spatial / GIS / neighbourhood boundaries, realtor and house pricing from a variety of sources including City, StatCanada and Teranet.

Results

We developed an AI solution that met the public and community health needs of this City by identifying individuals at risk of homelessness and provided web-based planning tools for optimal shelter service delivery (type, location, etc.) This solution has enabled the Shelters division of the City to better understand and anticipate the needs of their clients, enabling them to discover insights about the causes, effects, impacts and drivers that can help them pinpoint and identify solutions.

 Housing Affordability Surveillance: Example AIES web user interface for geo-spatial relevant view of Shelter Needs Index, Housing Affordability Index, etc.

Housing Affordability Surveillance: Example AIES web user interface for geo-spatial relevant view of Shelter Needs Index, Housing Affordability Index, etc.

Our solution has enabled the Shelters division to better understand and anticipate the needs of their clients, enabling them to discover insights about the causes, effects, impacts and drivers that can help them pinpoint and identify solutions.

Other Use Cases

DATA CURATION & INTEGRATION

DEMOGRAPHICS

SPATIAL ANALYSIS

GEOGRAPHICAL ANALYSIS