Eyes of Things

Area of Science:

• Computer Science
• Electrical Engineering
• Robotics

Background:

• Embedded systems are crucial for monitoring and control, evolving towards connectivity for the Internet of Things (IoT).
• Increasingly, embedded devices require autonomous intelligence for complex problem-solving, with Computer Vision (CV) being key to interpreting visual data.
• The integration of CV in embedded systems unlocks potential in diverse fields like drones, robotics, and intelligent surveillance.

Purpose of the Study:

• To introduce the Eyes of Things (EoT) platform, a versatile solution designed for embedded computer vision.
• To address the challenges and opportunities presented by the integration of intelligent computing and CV in embedded systems.
• To facilitate the development of next-generation intelligent embedded devices for the Internet of Things.

Main Methods:

• Development of the Eyes of Things (EoT) platform, a specialized hardware and software system for embedded computer vision.
• Integration of advanced algorithms, potentially including deep learning, for real-time image and video analysis on edge devices.
• Focus on enabling autonomous intelligence within sensing and computing devices for enhanced data processing and decision-making.

Main Results:

• The EoT platform provides a versatile foundation for a wide range of embedded CV applications.
• Demonstrates the feasibility of deploying sophisticated CV capabilities on resource-constrained embedded systems.
• Highlights the potential for increased security, reduced latency, and lower power consumption through edge-based CV processing.

Conclusions:

• The Eyes of Things (EoT) platform is a significant advancement in enabling intelligent embedded systems.
• Embedded computer vision is poised to revolutionize numerous industries through applications in IoT, robotics, and beyond.
• The future of embedded systems lies in their ability to autonomously perceive and interpret the world using computer vision.