Integrating Computer Vision, Edge Computing, and IoT on Raspberry Pi HMIs

Introduction

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.

Seeed Studios’ Raspberry Pi HMIs offer a transformative solution for achieving gateway intelligence and on-device IoT seamlessly. These HMIs, driven by Raspberry Pi, 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.

We are going to explore different applications in security, surveillance, and manufacturing domains where we can use computer vision and IoT capabilities.

Security and Surveillance Systems

Anomaly detection 

Figure: Smart Parking System with anomaly parking detection

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. 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.

Video Surveillance and Security

Figure: Face Detection

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, 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.

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. 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.

Manufacturing Cases

Enhancing Safety of the Workplace

Figure: PPE Kit Detection using YoloV5

Ensuring the safety of the workforce in manufacturing is critical for both employee well-being and production efficiency. Manual monitoring processes are prone to errors, as individuals may struggle to observe multiple screens simultaneously, leading to potential consequences for workers and the overall manufacturing firm. Computer vision technologies address this challenge by efficiently detecting safety issues, generating reports in dashboards, and issuing automatic alerts in the event of accidents. This proactive approach enables timely intervention by management, promoting a safer work environment and minimizing the impact of potential incidents on production.

Combat Viral disasters and Ensure people’s health 

Figure: Face Mask Detection

During the COVID-19 pandemic, manufacturing plants faced disruptions, and upon resuming activities, safety measures such as social distancing and mask-wearing became imperative. Computer vision applications emerged as crucial tools for monitoring and enforcing these protocols. By employing deep learning models, computer vision enables effective monitoring of workforce compliance with COVID-19 measures, such as social distancing detection. This technology ensures a safe working environment during and post-pandemic. An additional application involves automated mask control, efficiently detecting individuals without masks.

Quality Controlling 

Using computer vision in manufacturing is great because it can find even tiny defects that might be hard for people to see while making things. Finding and fixing these problems is super important to stop bad products from going to customers. This helps avoid spending more money on production and keeps customers happy. With computer vision, manufacturers can keep a close eye on the production process, catching any defective pieces and making sure the products are of good quality. This not only makes sure everything is good quality but also helps the business look good by stopping bad products from reaching customers.

Seeed Studio’s Raspberry Pi Ecosystem

Seeed Studio has been serving the Raspberry Pi user community since 2013 and took the lead to join the approved reseller and design partner. Since the first version of reTerminal in 2021, we have a series of products including reRouteredge controller series, and this year reTerminal DM, serving creators, makers, enthusiasts, students, engineers, enterprises as well as industries, and every scenario needing Raspberry Pi. 

More Resources

About Author

4 thoughts on “Integrating Computer Vision, Edge Computing, and IoT on Raspberry Pi HMIs

  1. Saudações, Está à procura de um site oficial de apostas online fiável? Recomendo aquelas que oferecem uma interface de fácil utilização, pagamentos rápidos e uma vasta gama de desportos em que pode apostar. Dica extra: pesquise os seus sistemas de segurança e proteção de dados para se certificar de que as suas informações pessoais estão seguras.

  2. Integrating Computer Vision, Edge Computing, and IoT on Raspberry Pi HMIs (Human-Machine Interfaces) cable and internet packages directv enables powerful and efficient data processing and interaction. This convergence allows for real-time analysis of visual data, local decision-making, and seamless communication with IoT devices, enhancing automation and intelligence in various applications.

Leave a Reply

Your email address will not be published. Required fields are marked *

Calendar

January 2024
M T W T F S S
1234567
891011121314
15161718192021
22232425262728
293031