Celebrating Innovation: Unveiling the Winners and Highlights from the Nx EVOS Hackathon - Network Optix

Network Optix is ecstatic to announce the winners of our recent Nx EVOS Hackathon, where nearly 1,800 talented developers competed for a grand prize of $5,000. These teams showcased their creativity and technical prowess, highlighting the future of computer vision. Their work demonstrated how developers and organizations can harness Network Optix's Enterprise Video Operating System, Nx EVOS, to streamline the development of scalable vision AI applications. Let's take a quick glimpse into the competition and the innovative solutions that emerged as our winners.

Overview of the Competition

As camera quality and AI models advance, the potential for Video AI models to enhance operations grows exponentially. With this foresight in mind, Network Optix challenged participants to create impactful and inspiring computer vision applications using Nx EVOS. The goal was to fully automate tasks that traditionally require human perception and reasoning, such as monitoring unattended tables in restaurants, automating inventory shelf counts in grocery stores, and overseeing assembly lines for defects and irregularities. Participants were given access to Nx Toolkit, a suite of open developer tools included in Nx EVOS, to build reliable, scalable, and maintainable applications for a use case of their choice.

First Place: ShopkAIper

Our grand prize winner, created by VisionNXT, is ShopkAIper, an AI-powered retail management solution that aims to optimize retail management and improve customer satisfaction. By leveraging advanced computer vision technology and real-time video analysis, ShopkAIper provides valuable insights and alerts to help store managers make informed decisions. Key features include:

• Customer Dwell Time Analysis - Gain insight into the areas of the store where customers spend the most time and their subsequent purchasing decisions in these areas.
• Identification of Frequently Co-purchased Products - Monitor and analyze items that are often bought together to further optimize product placement and future marketing strategies.
• Anomaly Detection for Potential Thefts - Identify discrepancies between shelf counts and inventory records to quickly detect and address potential theft.
• Ranking of Best-Selling Products - Track top-selling items to ensure timely restocking and maintain optimal inventory levels.

This innovative solution fully automates a large portion of daily store operations, offering a competitive edge and increasing revenue through data-driven strategies.

Second Place: GARUD

In second place we have BroBots with their GARUD (Geo-spatial Animal Reckon User Dashboard). This submission was designed to improve wildlife management in both national parks and the wild, utilizing drones, cameras, and Nx EVOS to identify and provide real-time video streams of local wildlife, assisting rangers, tourists, and researchers. Key functionalities include:

• Wildlife Identification, Detection, and Location Mapping - Utilizes AI technology to identify and track wildlife, automatically mapping their locations for comprehensive monitoring.
• Real-Time Streams of Detected Wildlife - Allows access to live footage of tracked wildlife, providing up-to-date information on their condition and behavior.
• Potential Poaching Alerts - Detects potential poachers in the area to enhance response times and bolster conservation efforts. 

GARUD enhances the ability to monitor and protect wildlife, ensuring a safer environment for animals and providing valuable data for researchers and tourists.

Third Place: Parking Slot Detection and Occupancy Monitoring

Our third place winner, Parking Slot Detection and Occupancy Monitoring System by ThingTank, addresses the challenge of finding vacant parking spots in busy lots by using security camera footage to detect parking slot occupancy in real-time. This allows parking lot security to watch for potential security issues and customers to quickly identify vacant spots. The system offers:

• Optimized Parking Space Utilization - Leverage deep learning systems to swiftly identify available parking spots, streamlining the parking process.
• Cost-Effective and Low-Maintenance Solution - Utilize existing video cameras instead of costly and maintenance-intensive sensors to monitor parking lots.
• Improved Accuracy and Reduced Errors in Parking Management - Empower site managers to optimize parking lot utilization with greater accuracy and fewer errors.
• Fire Detection Integration - Detect potential accidents and vehicle fires early, preventing escalation and enhancing safety.

By leveraging deep learning algorithms, this application provides a seamless and efficient way to manage parking facilities, enhancing the overall experience for drivers and facility operators.

Congratulations to Our Winners!

We extend our sincerest congratulations to the winners of the Nx EVOS Hackathon. Their innovative solutions demonstrate the transformative power of Computer Vision in addressing real-world challenges. We look forward to seeing these applications come to life and advance their respective fields in the future.

Stay tuned for more updates and success stories as we continue to explore the limitless potential of Nx EVOS and celebrate the brilliant minds driving technological advancements.