Emergency Connect System Research Paper

Efficient emergency response remains a major challenge in rapidly expanding urban environments such as Indore, where even minor delays in locating and contacting the nearest police station, hospital, fire station, or petrol pump can significantly influence survival outcomes. As population density increases and mobility patterns become more complex, existing emergency access platforms struggle to provide fast, accurate, and reliable assistance. Widely used solutions such as Google Maps and 112 India suffer from multi-step search processes, unverified or outdated emergency data, centralized call routing delays, and complete dependency on stable network connectivity. These limitations create substantial response bottlenecks, especially during panic situations, low-signal conditions, or disaster-induced outages. To address these deficiencies, this research introduces Emergency Connect, a localized, geospatially optimized, and offline-capable emergency response system specifically developed for Indore. The system minimizes user interaction, enhances geolocation precision, and ensures uninterrupted accessibility. Emergency Connect integrates four core components: real-time GPS acquisition, PostGIS-based nearest-service computation, a one-tap emergency calling interface, and SQLite-backed offline data storage. This architecture enables the application to provide a seamless user experience even in scenarios where conventional platforms fail. A key innovation of Emergency Connect lies in its use of PostGIS K-Nearest Neighbor (KNN) geospatial indexing, which significantly accelerates nearest-emergency-service discovery by computing optimized results within milliseconds. Additionally, the system employs a manually verified, city-specific emergency database to eliminate inaccuracies commonly found in user-generated public listings. The offline-first design ensures that all essential emergency information—including phone numbers and coordinates—remains accessible without internet connectivity, guaranteeing reliable performance in remote areas, congested zones, and disaster conditions. To evaluate the system’s performance, extensive field testing was conducted across 15 diverse locations in Indore, representing dense urban regions, semi-urban environments, highways, and low-signal areas. Tests were performed under strong network, weak network, fluctuating connectivity, and complete offline conditions across multiple smartphone models. Performance metrics were compared against Google Maps and 112 India using four parameters: time-to-contact, geolocation accuracy, latency, and offline behavior. Experimental results show that Emergency Connect reduces time-to-contact by 62–78%, lowering the response initiation time to 5–8 seconds, compared to 25–40 seconds in Google Maps and 20–30 seconds in 112 India. Geolocation accuracy improved by 40–55%, largely due to the use of validated coordinates and geospatial ranking. Latency improved by 3×–5×, particularly under low-signal conditions, demonstrating superior responsiveness. Most significantly, Emergency Connect maintained 91% functionality in offline mode, offering uninterrupted access to emergency contacts and approximate distance calculations even without connectivity. These results validate Emergency Connect as a high-performance, resilient, and scalable emergency management solution. By combining speed, accuracy, ease of use, and offline reliability, the system addresses critical shortcomings in existing platforms and establishes a practical foundation for city-specific emergency response technology. The findings highlight the potential for expanding Emergency Connect to other cities, paving the way for more efficient, accessible, and technologically robust emergency systems across urban India.