CrisisGuard

CrisisGuard: Our Journey to Building an AI-Powered Safety System

Inspiration:

Our project, CrisisGuard, was born out of a collective commitment to making a tangible impact on safety and emergency prevention. From the beginning, our team’s dedication to improving the lives of others motivated every decision. The passion and collaborative spirit shared by all of us fueled the drive to create a solution capable of protecting homes, businesses, and communities from unforeseen disasters.

What it does:

CrisisGuard leverages Prolog and sCASP to analyze real-time data, enabling it to identify and mitigate critical risks such as fires, power outages, break-ins, and floods. By detecting these threats early, the system takes preventive actions to safeguard both people and property before disaster strikes.

How we built it:

The development of CrisisGuard was a truly collaborative effort. Through teamwork, we brought together our collective strengths in programming, logic, and problem-solving to build a robust, AI-powered safety system. Every decision throughout the process was informed by real-time data analysis and a structured approach to risk prediction and prevention.

Challenges we ran into:

One of the most rewarding aspects of our journey was that, overall, we faced few significant challenges. This success was due to our team's strong communication, adaptability, and shared problem-solving mindset. We tackled any obstacles that arose with determination and kept the project moving forward without major setbacks.

Accomplishments that we're proud of:

We are incredibly proud of developing a fully functional AI-powered system that integrates advanced technologies like Prolog and sCASP. CrisisGuard is capable of predicting and preventing a wide range of disasters, offering a concrete solution to improve safety. Our ability to collaborate seamlessly and accelerate development has also been a key achievement.

What we learned:

Throughout the course of this project, we learned valuable lessons—especially in the areas of Prolog and sCASP. These technologies allowed us to apply logical reasoning to solve complex, real-time problems. More importantly, we learned the immense power of teamwork: how blending diverse skills and perspectives fosters innovative solutions and drives progress.

What's next for CrisisGuard:

Looking ahead, we plan to expand CrisisGuard's capabilities by incorporating even more types of emergencies and broadening its coverage. We are exploring the integration of machine learning to enhance predictive accuracy, allowing for even earlier intervention. Additionally, we’re actively seeking potential partnerships to bring CrisisGuard into real-world applications, helping to protect communities on a larger scale.

Our NETIDs

SXK230361 JXA230071 MKS220004

Built With

• prolog
• swish