The problem ResqAI solves

In emergency situations, every second counts. However, when the emergency call center is overwhelmed or understaffed, callers may have to wait for a long time before their call is answered. This delay can be critical and could result in a loss of life or property. Our hackathon project, ResqAI, solves this problem by using artificial intelligence to grade the importance of each call and transfer the relevant information to the emergency operator. This helps emergency services to respond more efficiently and effectively, potentially saving lives and reducing property damage.

The Features which we have in ResqAI :

• AI-powered call management: ResqAI uses natural language processing (NLP) and machine learning (ML) to identify the urgency of each call and prioritize them accordingly.
• Call grading based on keywords: ResqAI grades each call based on the keywords spoken by the caller. This allows the system to quickly identify urgent calls and transfer them to the emergency handler.
• Location tracking: ResqAI also records the location of each caller and provides this information to the handler.
• Call transcript: ResqAI provides a transcript of each call to the emergency handler, allowing them to quickly and accurately assess the situation and respond accordingly.
• Automated responses: In some cases, ResqAI can provide automated responses to callers to guide them through emergency situations until an emergency handler is available.

Challenges we ran into

Some of the challenges we faced were in the areas of voice recognition, the Ethereum implementation and some of the backend integration with the frontend ofour application.