Over 3 lakh emergencies are occurring everyday where over 9.5% of the population is being affected by an emergency each year. The World Health Organization projected that by 2020, road crashes will become a major killer in India, accounting for more than 175,000 deaths per year We aim to improve the effectiveness and success rate of the emergency service responding within the golden hour to maximize its efficiency.
What it does
Save A Life Maps is a mobile application which notifies users in transit that are along the path of an Emergency Service Provider (ESP) to make way for the incoming ESP such as an Ambulance, fire brigade, etc.
Our solution has a threefold purpose:
Helps users avail emergency services. Triangulates and dispatches the nearest ESP the user availed.
Connects the emergency service dispatch to the user in need and provides an optimised route with our pathfinding algorithm that works in real time.
Notifies users along the way of the ESP’s path to move out of the way in advance to ensure that a clear route is provided.
When an emergency has occurred, (for example a medical emergency such as a cardiac arrest or an accident) the general public user can report this situation on the app, where they can request for an emergency vehicle to be dispatched (an ambulance in this case) with their precise location being shared with just a single tap on the application. A notification is then broadcasted to all the nearby ESPs that are registered with the application. The first available ESP to accept this request will be provided with the user’s location and contact details. An optimum route is then generated for the ESP so that they can reach the place of emergency in time. The user who reported this emergency will get information on the ambulance details and the ETA (Estimated Time of Arrival) and can track the ESP in real time.
How we built it
Invented a novel path clearance algorithm using google maps API. Developed a web prototype that served as proof of concept of the algorithm. Developed a system architecture which uses a microservices approach. Made a flutter application to develop cross platform applications for Android, iOS, Linux, macOS, Windows, Google Fuchsia, and the web from a single code-base. Located the nearest ambulance and the hospital around a user in need. Worked on several threshold and edge cases for the ESP.
Challenges we ran into
1) Devising the best risk-averse notification system.
2) Adapting to the varying response times and experience levels of drivers on road.
3) Devising a good microservices approach.
Accomplishments that we're proud of
1) Invented novel path clearance algorithm.
2) Targeting only the users in transit along the path of the ESP and successfully sending them notifications.
3) Working with multiple ESPs simultaneously and handling several edge cases.
4) Developed an entire system architecture promoting re-usability of code.
5) Developed a risk averse notification system using two methods:
method 1: Using two notifications when a user is detected to be along the path of an ESP. The first notification informs the user to get ready to make way while the second notification that follows shortly after finally informs the user to make way for the incoming ESP.
method 2: changing the color of the polyline object to orange to inform the user to get ready to make way and then shortly after to dark green to ask them to finally make way.
6) There will also be a custom audio for each of the notifications for any user who has enabled audio navigation.
7) Provided an emergency button for users that can avail any emergency service on a single tap.
8) triangulated the nearest emergency service to the user in need and dispatched it with the optimal route.
9) Notified all the traffic police stationed along the path in cases of heavy traffic congestion to help clear traffic manually.
10) Provided users with a confirmation along with the ETA once the ESP is dispatched.
11) Provided the users with an option to track the ESP in real time and included the numbers of the paramedics assisting the drivers in case the user requires immediate relief.
12) Re-purpose the application for organ transportation.
13) Handled several edge cases such as:
i) Ambulance that exceeds the ETA resulting in re-dispatching another ambulance,
ii) multiple ambulances at crossroads,
iii) In multi-lane roads we only notify the users travelling along the path of the incoming ESP and not the users travelling in the opposite direction.
14) Developed a showcase web application to allow new users to acquaint themselves with the platform and experience the notification system beforehand.
15) Further reduced distractions by enabling vibration based notifications i.e. 2 vibrations to get ready and 3 vibrations to finally make way. This is optional for users to enable based on their preferences and mode of transportation.
What we learned
1) Learning from documentation.
2) Implementing google maps APIs such as Routes API, Geolocation, and Direction APIs.
3) Incorporating driver psychology.
4) Reality-centric development.
5) Built soft skills such as team work, leadership, project planning, and management.
What's next for Save A Life Maps
1) Focus on stress testing and building an end to end product.
2) Finally, we will work on the scalability of the application using Kubernetees.
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