{"id":91602,"date":"2024-01-30T09:40:50","date_gmt":"2024-01-30T09:40:50","guid":{"rendered":"https:\/\/www.seeedstudio.com\/blog\/?p=91602"},"modified":"2024-01-31T01:59:11","modified_gmt":"2024-01-31T01:59:11","slug":"integrating-computer-vision-edge-computing-and-iot-on-raspberry-pi-hmis","status":"publish","type":"post","link":"https:\/\/www.seeedstudio.com\/blog\/2024\/01\/30\/integrating-computer-vision-edge-computing-and-iot-on-raspberry-pi-hmis\/","title":{"rendered":"Integrating\u00a0Computer\u00a0Vision,\u00a0Edge\u00a0Computing,\u00a0and IoT on\u00a0Raspberry\u00a0Pi\u00a0HMIs"},"content":{"rendered":"\n

Introduction <\/h2>\n\n\n\n

In recent times, advancements in deep learning and edge computing have revolutionized the realm of computer vision, particularly in surveillance, security, and manufacturing. The adoption of Edge AI, integrating on-device machine learning with localized processing, has overcome challenges such as network issues and privacy concerns. This decentralized approach not only boosts system robustness but also makes real-time computer vision more practical and cost-effective. The seamless integration with IoT further elevates system intelligence, enabling a comprehensive and connected approach to data analysis in diverse applications.<\/p>\n\n\n\n

Seeed Studios’ Raspberry Pi HMIs<\/a> offer a transformative solution for achieving gateway intelligence and on-device IoT<\/font><\/strong> seamlessly. These HMIs, driven by Raspberry Pi<\/a>, act as intelligent gateways, processing data locally with efficiency. The integration of gateway intelligence empowers devices to autonomously make informed decisions, enhancing real-time responsiveness. The synergy between Seeed Studios’ hardware and Raspberry Pi capabilities establishes a sturdy foundation for deploying comprehensive IoT solutions directly at the edge, ensuring efficiency and speed in data processing.<\/p>\n\n\n\n

We are going to explore different applications in security, surveillance, and manufacturing domains where we can use computer vision and IoT capabilities.<\/p>\n\n\n\n

Security and Surveillance System<\/strong>s<\/h2>\n\n\n\n

Anomaly detection <\/strong><\/h3>\n\n\n\n
Figure: Smart Parking System with anomaly parking detection <\/figcaption><\/figure>\n\n\n\n

Computer vision understands unusual behavior in surveillance by learning from data, using different types of learning. It’s used for spotting strange vehicle presence or sudden crowd movements<\/font><\/strong>. Anomaly detection systems use data and specific learning to find anomalies, which can be things like a single-point anomaly (like a non-moving car) or contextual anomalies (normal behavior in a different context). They’re also classified as global (happening without a specific location) or local (within a specific area). Security monitoring covers various areas like traffic, subways, campuses, trains, boats, buildings, and public spaces. It helps detect things like stopped vehicles, panic situations, unauthorized access, and unusual pedestrian behavior.<\/p>\n\n\n\n

Video Surveillance and Security<\/strong><\/h3>\n\n\n\n
Figure: Face Detection<\/figcaption><\/figure>\n\n\n\n

Smart video surveillance has many uses, like spotting unusual activities, tracking objects, and analyzing movements. Cooperative video surveillance uses multiple cameras for big AI vision systems. People detection systems, using algorithms like YOLOv7\/v5<\/font><\/strong>, automatically identify single or multiple persons for security. Movement analysis, combining human detection and path modeling, helps predict and understand vehicle and pedestrian behavior in Smart Cities<\/font><\/strong>.<\/p>\n\n\n\n

Facial recognition boosts security by automatically identifying people, but it needs strong privacy safeguards. Identifying human actions and spotting motion patterns help catch illegal activities like littering or loitering<\/font><\/strong>. For driver and traffic safety, cameras on the road or on vehicles detect anomalies like lane departures or pedestrians. In-car safety systems watch drivers for signs of tiredness or not following rules, making everything safer<\/font><\/strong>.<\/p>\n\n\n\n

Manufacturing Cases<\/strong><\/h2>\n\n\n\n

Enhancing Safety of the Workplace<\/strong><\/h3>\n\n\n\n