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Power BI Embedded
Power BI includes a very powerful method for sharing called Power BI Embedded. This method of sharing is powerful because you can share Power BI...
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Embedded Systems: Rules to Improve Adaptability
Embedded systems have specific properties, which are consequences of the application domain, namely the close connection to the underlying technical...
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Models of Embedded Systems
This chapter covers models of embedded systems. First, it describes and demonstrates the simple super-loop system model and points out its...
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SDK4ED: a platform for building energy efficient, dependable, and maintainable embedded software
Develo** embedded software applications is a challenging task, chiefly due to the limitations that are imposed by the hardware devices or platforms...
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LExCI: A framework for reinforcement learning with embedded systems
Advances in artificial intelligence (AI) have led to its application in many areas of everyday life. In the context of control engineering,...
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Coconut: Typestates for Embedded Systems
Typestate programming defines object states and actions to improve software safety by ensuring operations on objects follow the correct sequence....
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Cloud data security for distributed embedded systems using machine learning and cryptography
In the growing demand for distributed embedded systems that efficiently execute complex processes and high-end applications, safeguarding sensitive...
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An embedded device-oriented fatigue driving detection method based on a YOLOv5s
Currently, most fatigue driving detection methods rely on complex neural networks whose feasibility in hardware implementation needs to be further...
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A middleware for providing communicability to Embedded MAS based on the lack of connectivity
An Embedded multi-agent system (Embedded MAS) is an embedded cognitive system based on agents cooperating to control hardware devices. These agents...
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Embedded Object Detection and Map** in Soft Materials Using Optical Tactile Sensing
In this paper, we present a methodology that uses an optical tactile sensor for efficient tactile exploration of embedded objects within soft...
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Embedded and real time vehicle classification system with occlusion handling
The idea of applying AI in embedded systems is growing in all sectors, from airplanes to drones, cars, cell phones and robots. The challenge for this...
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Embedded topics in the stochastic block model
Communication networks such as emails or social networks are now ubiquitous and their analysis has become a strategic field. In many applications,...
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Embedded Robotics From Mobile Robots to Autonomous Vehicles with Raspberry Pi and Arduino
This textbook presents a unique examination of mobile robots and autonomous vehicles using embedded systems, from introductory to advanced level. It...
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Task ordering in multiprocessor embedded system using a novel hybrid optimization model
In a multiprocessor system, the task scheduling function is a vital performance to minimize many issues. A multiprocessor system is applicable for...
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Neural network-based small cursor detection for embedded assistive technology
Assistive technology (AT) is invaluable to people with special educational needs and disabilities, enabling them to interact with computers more...
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Emotion aided multi-task framework for video embedded misinformation detection
Online news consumption via social media platforms has accelerated the growth of digital journalism. Adverse to traditional media, digital media has...
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Efficient memory reuse methodology for CNN-based real-time image processing in mobile-embedded systems
Real-time image processing applications such as intelligent security and traffic management requires pattern recognition tasks, such face...
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Real-time attention-based embedded LSTM for dynamic sign language recognition on edge devices
Sign language recognition attempts to recognize meaningful hand gesture movements and is a significant solution for intelligent communication across...
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Safety-Critical and Embedded Systems Architectures
In this chapter we look at the specific architectural issues involved in safety-critical systems (SCS), and design approaches for SCS. Because SCS...
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A Deep Learning Framework for Microarchitecture Independent Workload Characterization Technique for Multi-core Asymmetric Embedded Systems
Embedded workloads are increasing day by day and becoming more complex. The number of workloads running in the embedded processors has been growing...
