Ambulance Dispatch System with Traffic Light Coordination
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Solution Overview
Problem
Ambulance delays due to traffic congestion result in significant casualties and injuries, highlighting the need for an efficient and consistent smart rescue system.
Innovation Solution
A server-controlled smart rescue system that integrates a geo-location system, notification system, navigation system, and microchip technology in traffic lights to quickly dispatch ambulances and optimize their routes, thereby reducing delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If ambulances wait at traffic lights following normal traffic rules, then traffic light control system maintains order, but ambulance arrival time increases due to delays
Solution Approach 1:
The system performs preliminary actions by detecting upcoming traffic lights in advance (up to 2 km distance) and pre-coordinating with traffic control centers to adjust signal timing before the ambulance arrives, ensuring green lights are activated in advance to eliminate waiting time
Solution Approach 2:
The traffic light control system acts as an intermediary between the ambulance navigation system and actual traffic signals. The navigation system communicates with traffic control centers, which then adjust traffic light timing to accommodate ambulance passage, mediating between normal traffic flow and emergency vehicle priority
2Productivity
If a smart rescue system with real-time tracking and traffic light control is implemented, then ambulance dispatch efficiency improves, but system complexity increases
Solution Approach 1:
The system integrates multiple functions into unified components: the server handles ambulance tracking, route optimization, traffic light coordination, and hospital routing simultaneously; the mobile application provides request submission, tracking, and communication functions in one interface, reducing overall system complexity through consolidation
Solution Approach 2:
The system implements continuous feedback loops where the server receives real-time location data from ambulances, calculates optimal routes, communicates with traffic control centers, and adjusts routing decisions based on traffic conditions and ambulance progress, enabling adaptive optimization without excessive complexity
3Loss of time
If the navigation system recognizes traffic lights up to 2 km in advance, then ambulance can prepare for signal optimization, but measurement precision requirements increase
Solution Approach 1:
The navigation system performs preliminary detection of traffic lights at long distances (2 km) in advance of the ambulance arrival, allowing sufficient time for coordination with traffic control centers to adjust signal timing before the ambulance reaches the intersection
Solution Approach 2:
The system transitions from reactive traffic light response to proactive detection by adding the time dimension - detecting and coordinating traffic light adjustments well in advance of arrival, transforming the problem from immediate reaction to scheduled optimization
Data Source
AI summary
A smart rescue system 100 is disclosed. The system 100 includes a mobile device 101 allowing a requester to request for ambulance services, a network 102, and a server 103 communicatively coupled with the mobile device 101 through network 102. The requester provides details including patient's address. The server 103 includes a geo-location system 104 to automatically determine the ambulance available in a geo-spatial vicinity of the patient's address, a notification system 106 to notify a driver of the ambulance available in a geo-spatial vicinity of the requested address, a navigation system 105 to navigate the driver to a nearest medical centre in a geo-spatial vicinity of the patient's address, and recognizes upcoming traffic lights up to a certain distance in advance, and a microchip technology 107 fitted in the traffic lights controlled by the server 103.