<scp>AI</scp> ‐Driven Smart Neighborhood Services: A Real‐Time Geospatial Booking Platform for Emergency and On‐Demand Service Delivery

ABSTRACT The problem of connecting users with verified local service providers quickly has been a significant issue in the era of urban digital transformation, particularly in emergencies. Conventional techniques of service discovery, for example, Directory or ad hoc mobile applications, cannot provide real‐time responsiveness, intelligent character prioritization, and accurate location. The AI‐Driven Smart Neighborhood Services is an affordable, highly evolved real‐time booking and online service and represents a complex geospatial intelligence, intelligent scheduling, and Progressive Web App (PWA) technology that can make it easy to discover and book professionals near their home or work areas. The technology incorporates the AI‐enhanced Haversine formula and the K‐Nearest Neighbor (KNN) algorithm to facilitate dynamic proximity matching, optimize booking scheduling using a Priority Queue, and employ a Bayesian average rating to ensure fair and impartial ranking of providers. The system is constructed on an expandable architecture (Next.js, Firebase Firestore, Google Maps API), which enables searching for emergency availability and provides a convenient user experience across all devices. The work provides a strong foundation for implementing geospatially aware, intelligent service platforms in a smart city ecosystem, where a gap exists between trusted local services and real‐time user demands.

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Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-10-24
DOI
https://doi.org/10.1002/cpe.70391
Citations
2
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
4.35
Controls
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article

AI ‐Driven Smart Neighborhood Services: A Real‐Time Geospatial Booking Platform for Emergency and On‐Demand Service Delivery

V. Padmavathi, R. Kanimozhi
2 citations
Concurrency and Computation Practice and Experience
Human Mobility and Location-Based Analysis
4.35
article

AI ‐Driven Smart Neighborhood Services: A Real‐Time Geospatial Booking Platform for Emergency and On‐Demand Service Delivery

V. Padmavathi, R. Kanimozhi
article en
2 citations

Abstract

ABSTRACT The problem of connecting users with verified local service providers quickly has been a significant issue in the era of urban digital transformation, particularly in emergencies. Conventional techniques of service discovery, for example, Directory or ad hoc mobile applications, cannot provide real‐time responsiveness, intelligent character prioritization, and accurate location. The AI‐Driven Smart Neighborhood Services is an affordable, highly evolved real‐time booking and online service and represents a complex geospatial intelligence, intelligent scheduling, and Progressive Web App (PWA) technology that can make it easy to discover and book professionals near their home or work areas. The technology incorporates the AI‐enhanced Haversine formula and the K‐Nearest Neighbor (KNN) algorithm to facilitate dynamic proximity matching, optimize booking scheduling using a Priority Queue, and employ a Bayesian average rating to ensure fair and impartial ranking of providers. The system is constructed on an expandable architecture (Next.js, Firebase Firestore, Google Maps API), which enables searching for emergency availability and provides a convenient user experience across all devices. The work provides a strong foundation for implementing geospatially aware, intelligent service platforms in a smart city ecosystem, where a gap exists between trusted local services and real‐time user demands.

Concurrency and Computation Practice and ExperienceVol. 37(25-26)
Department of Biotechnology (IN)
Openalex Percentile: Top 6%
Human Mobility and Location-Based Analysis
4.35
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