Chukwudifu Okoroafor@engrokoroafor

EngageGov is an AI-driven citizen engagement app built using xAI's Grok models (grok-beta, grok-vision-beta), Python, OpenAI, and Streamlit, designed to enhance government efficiency and cut costs. The app allows citizens to report issues such as damaged infrastructure (e.g., bad roads or leaking pipes) and make inquiries about government services (e.g., how to apply for healthcare benefits or access education support) through text or photo submissions. By using sentiment analysis and Grok's AI capabilities, EngageGov analyzes each submission, providing tailored responses and routing issues to the appropriate government agency (e.g., Health, Transport, Infrastructure) via email or SMS for quick action. This reduces unnecessary manual work, making the process more streamlined and reducing administrative costs. For example, a citizen reporting a pothole can easily submit a photo, and the AI will analyze the urgency and forward the report to the Ministry of Transport for immediate attention. Similarly, when someone inquires about available government healthcare programs, Grok's AI will instantly suggest the necessary steps to subscribe, cutting down on the need for in-person inquiries. This app can help governments cut costs by reducing manual handling of complaints, minimizing unnecessary administrative resources, and ensuring efficient service delivery. By automating routine tasks and providing self-service capabilities, EngageGov optimizes government spending, ensuring resources are allocated more effectively while increasing accountability and transparency.

AiScan is a cutting-edge AI-driven tool designed to optimize network management by identifying vulnerabilities and recommending fixes. It aims to enhance the connectivity and security of public sector networks, particularly for under-served schools and health centers. A 2022 Statista report revealed global business losses of $1.2 trillion due to poor network security and unoptimized infrastructure. AiScan helps mitigate these losses by leveraging advanced AI-powered functionalities: - IP Scanning: Detects exposed devices and vulnerabilities in network infrastructure. - DNS Analysis: Detects configuration errors, potential DNS spoofing, and other threats. - Wi-Fi Network Scanning: Analyzes local Wi-Fi networks for weak points, such as unsecured configurations or unauthorized access. (Currently functional on local systems; web-based access is under development.) - Data Visualization: Chart.js is used to display signal analysis scores of all detected Wi-Fi networks, with each network represented as bar graphs, the height reflecting the Wi-Fi network analysis score. (Note: This feature is currently available for local system use, working in tandem with Bluetooth network scanning functionality, with plans to roll out to the web once the Bluetooth scanning feature is available on web platforms). - AI-Powered Insights: Machine learning interprets scan results, prioritizes threats, and provides actionable recommendations to improve network performance and security. By focusing on scalable and transparent network optimization, AiScan aligns with the hackathon's mission of creating sustainable solutions for public sector connectivity. The project uses open-source AI technologies, making it accessible and adaptable to diverse network scenarios.