As impressive as embedded cameras already are in their functionality, their true potential is only beginning to be unlocked through the integration of Artificial Intelligence (AI). Merging AI with embedded cameras amplifies their capabilities while paving the way for more intelligent and responsive visual systems. This promises to reimagine how machines see and interact with increasingly complex surroundings.
In this blog, let’s find out about the role of AI in embedded camera applications, the benefits, and the most popular use cases. You’ll also get information on EdgeECAM50_USB, e-con Systems’ latest edge AI smart USB camera.
How AI works in embedded camera applications
AI operates as the analytical engine that transforms vast streams of visual data into actionable insights. Upon capturing visuals, AI algorithms preprocess this data to enhance clarity, after which they extract relevant features- faces, objects, or patterns. Using pre-trained models, the AI system interprets what it observes, enabling timely decisions – ranging from object identification to anomaly detection.
The camera’s AI components also engage in a continuous learning process, refining their accuracy and adaptability over time. So, the camera’s responses evolve with its environment and user requirements.
Benefits of AI-based embedded cameras
Superior image quality
One of the primary benefits of integrating AI into embedded cameras is the significant improvement in image quality. Algorithms can automatically adjust settings based on lighting conditions, rectify distortions, and stabilize images in real time. Advanced AI models can even enhance dynamic range, reduce noise, and ensure the resultant image or video is crisp and clear, regardless of the initial capturing conditions.
AI can monitor the health of the camera’s components, predicting potential malfunctions or failures before they occur. This proactive approach ensures that the camera system remains in optimal condition, reducing downtime and maintenance costs. It alerts the user or system administrator about necessary interventions, ensuring longevity and uninterrupted operation.
Contrary to the belief that advanced functions consume more power, AI can optimize the camera’s operations to ensure power efficiency. Algorithms can decide when to record, analyze, or transmit data, thereby conserving energy. Additionally, AI chipsets designed specifically for embedded systems are optimized for energy efficiency, ensuring that the camera works longer on a single charge or reduces overall power consumption.
Customization and flexibility
AI brings a level of adaptability to embedded cameras. Users or developers can train their cameras for specific tasks, be it detecting a particular type of wildlife or monitoring machinery in a factory. As AI models can be updated and retrained, cameras can evolve with changing requirements, ensuring that they remain relevant and useful across various scenarios and over extended periods.
Storage is always a concern with cameras, especially high-resolution ones. AI can intelligently compress visual data, ensuring that it retains quality while occupying less storage space. Furthermore, AI can decide what data is essential and needs to be stored, versus what can be safely discarded, optimizing storage utilization even further.
Simple use cases of AI cameras
- Tube classification: AI-driven embedded cameras can differentiate between various types of tubes based on their size, color, markings, and other distinguishing features. This ensures that labs and medical facilities can sort and utilize the appropriate tubes for specific tests or procedures.
- Cap identification: AI cameras can identify and classify tube caps based on their color, shape, or any other unique identifiers. This aids in reducing errors in sample handling, ensuring that caps are correctly matched to their respective tubes.
- Liquid level detection: These AI cameras can analyze tubes and containers to detect the volume of liquid present. Through AI, even minute changes in liquid levels can be noticed, ensuring accuracy in tests, dosages, and other critical applications.
Remote patient monitoring
- Vital sign monitoring: Cameras equipped with AI can remotely monitor patients’ vital signs, such as heart rate or respiration rate, by analyzing subtle changes in skin color or chest movements. This helps in continuous monitoring without intrusive equipment.
- Fall detection: Especially important for elderly patients, these cameras can detect unusual movements or postures that indicate falls, triggering immediate alerts to caregivers or medical professionals.
- Medication adherence: The cameras can track if patients are taking their medications on time and in the right dosage, ensuring adherence to prescribed treatments.
Smart traffic management
- Traffic flow analysis: AI-based cameras can analyze real-time traffic conditions, helping in dynamically changing traffic light durations to optimize flow and reduce congestion.
- Accident detection and response: The system can instantly detect accidents or obstructions, alerting authorities and rerouting traffic as necessary.
- Vehicle classification: By classifying vehicles, from trucks to motorcycles, cities can implement dynamic tolling or understand roadway usage better.
- Facial recognition: Beyond the traditional methods, AI-enhanced cameras can recognize faces even in varying lighting conditions, angles, or with partial obstructions, ensuring secure access to facilities or systems.
- Gait analysis: By studying the unique way individuals walk, AI cameras can recognize and authenticate individuals, adding an additional layer of security.
- Emotion detection: In certain environments, like airports or secure facilities, detecting heightened emotions like stress or anger can be indicators of potential risks.
e-con Systems’ latest edge AI smart USB camera
EdgeECAM50_USB is an edge AI smart USB camera based on the 5MP low-noise onsemi® AR0521 CMOS image sensor. It is specially designed, developed, and manufactured by e-con Systems for pre-analytic tasks like pre-analytical tasks, such as tube classification, cap identification, liquid level detection, etc. EdgeECAM50_USB comes with a powerful dual-core processor for running AI/ML algorithms directly on-board. Thereby, it enables fast and accurate data processing without extra hardware.
Other highlights of EdgeECAM50_USB include:
- Advanced AI capabilities
- Support for frameworks like TensorFlow Lite Micro and DeepviewRT
- On-board ISP for auto-exposure, auto-white balance, etc.
- Compact form factor
- USB 2.0 interface
Also, in order to empower product developers, e-con Systems offers a Model Pack with a sample model (test tube cap detection), configurations, and post-processing modules. They can be loaded using the Edge-CAMView.
Suresh Madhu is the product marketing manager with 16+ years of experience in embedded product design, technical architecture, SOM product design, camera solutions, and product development. He has played an integral part in helping many customers build their products by integrating the right vision technology into them.