The evolution of low-cost embedded systems is growing exponentially; likewise, their use in robotics applications aims to achieve critical task execution by implementing sophisticated control and computer vision algorithms. We review the state-of-the-art strategies available for Tiny Machine Learning (TinyML) implementation to provide a complete overview using various existing embedded vision and control systems. Our discussion divides the article into four critical aspects that high-cost and low-cost embedded systems must include to execute real-time control and image processing tasks, applying TinyML techniques: Hardware Architecture, Vision System, Power Consumption, and Embedded Software Platform development environment. The advantages and disadvantages of the reviewed systems are presented. Subsequently, the perspectives of them for the next ten years are present. A basic TinyML implementation for embedded vision application using three low-cost embedded systems, Raspberry Pi Pico, ESP32, and Arduino Nano 33 BLE Sense, is presented for performance analysis.
Sentiment analysis utilizes Natural Language Processing (NLP) techniques to extract opinions from text, which is critical for businesses looking to refine strategies and better understand customer feedback. Understanding people’s sentiments about products through emotional tone a…
Modern smart grids are built based on top of advanced computing and networking technologies, where condition monitoring relies on secure cyberphysical connectivity. Over the network infrastructure, transported data containing confidential information, must be protected as smart g…
Hate speech is a complex topic that transcends language, culture, and even social spheres. Recently, the spread of hate speech on social media sites like Facebook has added a new layer of complexity to the issue of online safety and content moderation. This study seeks to minimiz…
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Background: Monitoring external load in team sports is essential for performance optimization, injury prevention, and individualized training prescription. Although Local Positioning Systems (LPS) are widely used for indoor athlete tracking, they require wearable devices and spec…
Financial fraud has become a critical challenge for modern financial systems due to the rapid growth of digital transactions, online banking services, and electronic payment platforms. Traditional rule-based fraud detection systems are increasingly inadequate in addressing the ev…