Journal of Embedded Systems & Its Applications ISSN: 3139-2296 (Online)

Authors:-Sudha Kumari, Vandana Pathak, Kirti Panchal

Abstract:- Driver weariness has emerged as one of the main factors in traffic accidents in recent years. A complete way of assessing driver fatigue is the condition of the driver's drowsiness. Therefore, it is crucial to identify drowsy driving in order to protect people and property. The creation of a system that can detect tiredness is the aim of this research. This prototype is a real-time system that records pictures continuously, evaluates the eye's condition using the described method, and issues a warning if required. Although there are several techniques to measure driver weariness, this method is completely non-intrusive and has no impact on the driver, revealing the driver's true condition. To detect fatigue, the persistence value of the eye is calculated. The driver is regarded as sleepy when their eye closure exceeds a particular threshold.

Keywords:- Driver fatigue, Fatigue detection, Driver monitoring system, Face detection.

Authors:- S. Suresh kumar, V. Y. S. S. Sudirpatnaikuni, J.Priyanka

Abstract:- Now-a-days most of the accidents are taking place because, of consuming alcohol before driving and drowsiness while driving. To overcome this problem, we are using alcohol detector in the helmet which detects the alcohol consumption of the person and sends the message to the nearby police stations. To overcome the drowsiness situation, we use an IR sensor when a person is in drowsy state, then the sensor activates the buzzer near the ear. Thus, he can regain the consciousness. If the person wearing the helmet met with an accident then the vibrator circuit activates and the message will be sent to family members and to the nearby hospitals.

Keywords:- consuming alcohol before driving,drowsiness situation,sensor activates,regain the consciousness.

Authors:- P. Rahila , Varsha Narmadha 

Abstract:- The cost of testing the system is reduced when requirements are verified early in the development process. In this work, we examine the various methodologies for verifying model-based embedded system requirements. Different modeling languages have their own development and code generating tools. The developer may grasp the needs of hardware and software to create the system by selecting the appropriate tool during the design stage of an embedded system. For the development of safety-critical embedded systems, verification and code creation will be more useful. To create dependable embedded software code, modeling languages might be employed. However, the applicability of validated produced code is dependent on embedded software developers.

Keywords:- Model-based design, verification, and code generation are all aspects of embedded systems.

Authors:-Himani R Rajput , Geetanjali Rathore , Kusum Pawar 

Abstract:-The research offers an intelligent irrigation system with water and energy monitoring in order to reduce long-term water and energy use. It also reduces the need for constant human involvement in the field. Agriculture contributes significantly to a country's economic growth. Using water resources properly and efficiently for agriculture will help to conserve ground water supplies in the long run. In addition, energy management is an important component that was considered when creating this system. In a traditional irrigation system, the farmer must constantly monitor soil and weather conditions to ensure crop development. The suggested system measures several factors such as soil moisture, soil temperature, pH value, rainfall, humidity, and so on, and makes a judgement based on the sum of the parameters' values. Sensors for each of the aforementioned parameters generate continuous inputs for the system, which are compared to the reference values to create the system's control outputs. The amount of water and power consumed are continually measured in order to calculate the overall usage per month and warn the user. The land and weather conditions are constantly recorded for the farmer's future use.

Keywords: Intelligent irrigation, automated water supply, weather and soil based irrigation, rainfall detection, humidity based water flow

Authors:- Hiren Patel, M. Balamurugan

Abstract:- The concerns and factors associated with health are extremely important to man and are required for his life and functional thinking. As a result, a more sophisticated system capable of tracking and documenting changes in health indicators independent of time or place must be built. This research proposes a device capable of remotely monitoring heartbeat and breathing in real time. The goal of this project is to develop and build a low-cost adaptable heartbeat and respiration rate monitor alarm system utilising GSM technology. It is intended to show the patient's pulse and breath rate on an LCD before sounding an alarm and sending an SMS to the medical expert's or health personnel's mobile phone if and only if the heartbeat and breath rate threshold value is surpassed to a maximum. As a result, this approach suggests a continuous, real-time, secure, and exact monitoring of the patient's health. Its diagnosis of the patient's health and prevention of cardiovascular disease.

Keywords:- GSM technology, cardiac rate, parameters, real-time monitoring, sensors, SMS are all examples of emergencies.

Authors:- Preeti Kanojiya, S. R. Dharsana

Abstract:- In recent years, the majority of individuals have suffered from heart disease. Early identification of heart problems aids in accurate diagnosis. This model is used to screen patients' cardiac features on a regular basis. The heart rate is measured and classed as normal sinus rhythm, tachycardia, bradycardia, or atrial flutter. If any abnormalities are discovered during the study, the patient or cardiologist will be notified. This might be developed into a Point of Care device for use in rural areas and hospitals. The goal of this model is to provide a framework for community healthcare using a heart sound analysis system. This design incorporates several improvements, notably the efficient usage of a heart beat sensor. Medical doctors have also proposed that this sort of equipment might be effective in the early detection of prevalent heart illnesses.

Keywords:- Cardiovascular disease, Embedded System, Heartbeat Analysis, Care device

Author: Anjitha KB

Abstract: By every new day, alternative technologies are being developed, which in turn are helping to increase the speed of trains. Indian Railways aims to increase the speed of its passenger trains to 140180 km/h on conventional tracks. Thus it can be seen from the trending aspects of railways that they are primarily focusing on increasing the speed rather than the safety of the passengers. The primary focus should be the safety of passengers. Generally, it is seen that when a train compartment catches fire due to any reason, it's not easy to detect the fire initially and react to it. Due to this, the train does not stop instantly, which results in casualties and heavy damage to the train.

The objective of this paper is to design an Embedded Based Railway Train Safety System. This system consists of an Arduino, motor, fire and smoke sensor, alarm, and alert system. This paper proposes an embedded system that will be used to alert people so that life and damage can be minimized. If the train coach catches fire, the smoke sensor will sense it and send a signal to the Arduino. This activates the motor to pull the chain and activates an emergency alert system that sends an alert message to the train driver and guard room and activates the alarm. If the chain system to stop the train does not work properly, then even in that case, this system is very effective. So this system is useful to protect the precious lives of passengers and minimize the heavy damages due to fire accidents.

Keywords: Arduino, Embedded System, Fire, Passengers, Railway, Safety, Smoke sensor

Authors: Ankur Joshi, Shyam Lal Thakur, Harender Prasad, Gautam Verma

Abstract: Real-Time Operating Systems (RTOS) form the backbone of safety-critical systems, ensuring deterministic behavior and timely response under strict operational constraints. Safety-critical applications such as automotive control, medical devices, aerospace, and industrial automation depend heavily on RTOS to maintain system reliability and minimize risks. This paper reviews the recent advancements and optimization strategies in RTOS design, focusing on scheduling, resource management, fault tolerance, and security mechanisms. Various RTOS kernels and their performance in real-time applications are compared, highlighting the tradeoffs between efficiency, reliability, and maintainability. The study also emphasizes the significance of formal verification and predictive analysis in reducing system failures in safetycritical environments. Finally, the paper discusses emerging trends and challenges in RTOS optimization for future safety-critical applications.

Keywords: Real-Time Operating Systems, RTOS Optimization, Safety-Critical Systems, Task Scheduling, Fault Tolerance, Resource Management, Formal Verification

Authors: Aseem Setia, Ghanshyam Das Gupta

Abstract: Internet of Things (IoT) devices are increasingly used in smart homes, healthcare, agriculture, and industrial monitoring. These devices often operate on battery power for long periods, sometimes in remote or hard-to-reach locations. Therefore, designing low-power embedded systems has become a critical requirement in IoT development. Low power consumption not only increases battery life but also reduces maintenance cost and improves sustainability. This paper reviews various techniques, components, and architectural strategies used for low-power embedded system design in IoT devices. It discusses microcontroller selection, sleep modes, communication protocols, energy harvesting, software optimization, and power management strategies. The paper also provides tables and diagrams for better understanding of design approaches. The aim is to provide an overview of how engineers can design energy-efficient IoT nodes without compromising performance.

Keywords: Low power design, Embedded systems, IoT devices, Power management, Energy efficiency, Sleep modes, Microcontrollers, Energy harvesting

Authors: Gaurav Sharma, Devansh Kashyap, Manish Patil

Abstract: Cyber-Physical Systems (CPS) combine computation, networking, and physical processes. These systems are widely used in automotive control, healthcare devices, industrial automation, smart grids, and robotics. Traditional system design separates hardware and software development, which often leads to inefficiencies, timing issues, and higher costs. Hardware-Software Co-Design is an integrated design approach where both hardware and software components are developed together to meet performance, energy, cost, and timing constraints. This paper reviews the concept of hardware-software co-design for CPS, its methodologies, tools, challenges, and applications. Various partitioning techniques, modeling approaches, communication mechanisms, and real-time considerations are discussed. The paper also highlights how co-design improves system reliability and optimization in safetycritical CPS applications. Finally, future trends such as AI-driven design and reconfigurable architectures are explored.

Keywords: Cyber-Physical Systems, Hardware-Software Co-Design, Embedded Systems, Real-Time Systems, FPGA, System Optimization

Authors: Aseem Setia, Ghanshyam Das Gupta

Abstract: Field-Programmable Gate Arrays (FPGAs) have emerged as a pivotal technology for embedded systems in high-performance computing (HPC) applications. Unlike traditional processors, FPGAs provide hardware-level parallelism, configurability, and low-latency processing, making them suitable for computationally intensive tasks. This paper reviews the architecture, design methodologies, and application areas of FPGA-based embedded systems for HPC. It also explores performance comparisons with GPUs and CPUs, the challenges in integration, and emerging trends, such as FPGA-accelerated AI and reconfigurable HPC clusters. The paper concludes with insights into future research directions and design considerations for optimizing FPGA-based embedded systems.

Keywords: FPGA, Embedded Systems, High-Performance Computing, Hardware Acceleration, Reconfigurable Computing, Low-Latency Processing

Authors: Devender S Kaushik, Bibha Patil, Satyendra Tiwari

Abstract: Industrial automation relies heavily on embedded systems to manage processes, monitor equipment, and maintain high productivity levels. However, these systems are susceptible to faults due to hardware failures, software bugs, environmental disturbances, and communication errors. Fault-tolerant embedded systems (FTES) are designed to continue operating correctly even in the presence of such faults, thereby enhancing reliability, safety, and efficiency. This paper reviews the design principles, architectures, fault detection and recovery techniques, and applications of fault-tolerant embedded systems in industrial automation. Recent advancements, including redundancy methods, formal verification, and AI-assisted fault management, are discussed. Case studies from manufacturing, robotics, and process control demonstrate practical implementations. The paper concludes by highlighting emerging trends, challenges, and future research directions in this field.

Keywords Fault-tolerance, Embedded Systems, Industrial Automation, Reliability, Redundancy, RealTime Systems, Safety-Critical Systems

Authors: Upender Dhawan, Arjun Kale, Mahesh Patil, Sushil Rathor

Abstract: Embedded systems are widely used in modern applications such as wireless sensor networks, IoT devices, healthcare monitoring, environmental sensing and industrial automation. One of the major limitation of these systems is dependency on batteries which require periodic replacement or maintenance. In many cases like remote monitoring or hazardous areas, replacing batteries is difficult and costly. Energy harvesting provides a promising solution by converting ambient energy from environment into electrical energy to power embedded nodes. This paper reviews different energy harvesting techniques suitable for self-powered embedded systems including solar, thermal, vibration, RF, and wind energy harvesting. It also discusses power management strategies, storage elements, and design challenges in implementing energy harvesting in resource constrained nodes. Comparative analysis of different harvesting methods is presented with advantages and limitations. The paper also highlights recent trends and future directions in self-powered embedded nodes.

Keywords: Energy harvesting, Embedded systems, Self-powered nodes, IoT, Wireless sensor networks, Power management.

Authors: Dhawan S Nair, Jyoti Kulkarni, Pankaj K Jha, Suresh Baitha

Abstract: Real-time audio processing has become increasingly critical in applications ranging from mobile devices and hearing aids to live music processing and digital voice assistants. Embedded systems play a pivotal role in achieving low-latency, high-efficiency audio signal processing, particularly in resource-constrained environments. This paper presents a comprehensive review of embedded systems utilized for real-time audio processing, examining their architecture, processing techniques, hardware-software co-design, optimization methods, and application domains. Recent trends, including AI-assisted audio enhancement, low-power designs, and FPGA-based implementations, are also discussed. Challenges and future directions for embedded audio systems are highlighted, emphasizing the balance between computational performance and real-time constraints.

Keywords Embedded Systems, Real-Time Audio Processing, DSP, FPGA, Low-Latency, Audio Signal Processing, Edge AI, Microcontrollers

Authors: Rajan Pandey, Devender Singh, Ankush Tyagi

Abstract: Autonomous vehicles are one of the most advanced applications of embedded systems in the modern era. These vehicles rely on a complex integration of sensors, processors, communication modules and control units that operate together in real time. Embedded systems serve as the brain of autonomous vehicles, enabling perception, decision-making, navigation and control without human intervention. This paper reviews the role of embedded systems in autonomous vehicles, major hardware and software components, design challenges, real-time processing requirements, communication protocols, and safety concerns. The study also discusses how artificial intelligence, machine learning, and edge computing are integrated into embedded platforms to achieve efficient vehicle automation. Limitations such as power consumption, cybersecurity risks, and reliability issues are also discussed. The paper provides an overview of current technologies and future directions in embedded automotive systems.

Keywords: Embedded systems, autonomous vehicles, sensors, real-time processing, automotive control, IoT, machine learning, vehicle safety.

Authors: Riya Kulkarni , Manav Srivastav

Abstract: Wearable health monitoring devices are becoming very popular in recent years due to growth in embedded systems, low power electronics, wireless communication and smart sensors. These devices continuously track physiological parameters such as heart rate, body temperature, blood oxygen level, motion activity and many other health indicators. Embedded system design plays a very important role in making these wearable devices reliable, small in size, low power and comfortable for long time usage. This paper presents a detailed review of embedded system architecture, hardware components, software design, communication methods and power optimization techniques used in wearable health monitoring systems. Challenges like battery limitation, data accuracy, sensor calibration and security issues are also discussed. The paper also highlights recent trends such as AI integration, edge processing and IoT connectivity in wearable devices.

Keywords: Wearable devices, Embedded systems, Health monitoring, Sensors, Low power design, IoT, Edge computing

Authors: Pradeep Singh, Anmol Deshpande

Abstract: Smart grids and microgrids are modern solutions to overcome the limitations of conventional power systems. These systems depend heavily on embedded control systems for monitoring, protection, automation and real-time decision making. Embedded controllers are used for load balancing, voltage regulation, renewable energy integration and fault detection in distributed power networks. With increasing penetration of solar, wind and storage units, the need for intelligent embedded platforms has grown very much. This paper presents a detailed review of embedded control systems used in smart grids and microgrids. It discusses architecture, communication methods, control strategies, hardware platforms, and challenges. The role of real-time operating systems, IoT connectivity and distributed intelligence is also explored. Tables and diagrams are included to show system structure and component roles.

Keywords: Embedded systems, Smart grid, Microgrid, Real-time control, Distributed generation, IoT, Power electronics, Energy management.

Authors:- Prabhat Sharma, Devansh Kulkarni, Meenal Joseph, Arvind Jaiswal

Authors:-Edge Artificial Intelligence (Edge AI) is becoming an important paradigm where AI models are deployed directly on embedded devices instead of relying fully on cloud computing. This approach is very useful for real-time decision making, reduced latency, better privacy and lower bandwidth usage. However, embedded platforms such as microcontrollers, single board computers, and IoT devices usually have very limited computational power, memory, and energy resources. Running complex AI models on such platforms becomes a major technical challenge. This paper presents a review of techniques, architectures, optimization methods, and tools that enable deployment of Edge AI on resource-constrained embedded systems. It discusses model compression, quantization, pruning, hardware accelerators, and lightweight neural network architectures. The paper also highlights practical use cases, current challenges, and future research directions in this emerging field.

Keywords Edge AI, Embedded Systems, TinyML, Model Compression, Low-Power Devices, Quantization, IoT, Neural Networks

Authors: Tej Pratap Sinha , Sukhdev Vashu , Neeraj Chopra

Abstract: The growing reliance on embedded and IoT devices in critical applications has amplified the need for hardware-based security mechanisms. Hardware-Based Secure Boot (HBSB) and Trusted Execution Environments (TEEs) are essential technologies that ensure the integrity and confidentiality of software execution from system initialization to runtime. Secure Boot verifies the authenticity of firmware and operating systems during startup, preventing unauthorized code execution, while TEEs provide an isolated environment for sensitive computations and cryptographic operations. This paper provides a comprehensive review of hardware-based secure boot mechanisms and TEEs, exploring their architecture, implementation, advantages, challenges, and applications. The discussion includes comparative analyses, current research trends, and future directions for integrating these technologies in embedded systems, IoT devices, and edge computing platforms.

Keywords: Hardware Security, Secure Boot, Trusted Execution Environment, Embedded Systems, IoT Security, TPM, ARM TrustZone 

Authors: Ritika S. Patil, Mohan K. Devre, Afsana Parveen

Abstract: Embedded sensor networks are widely used in smart cities, healthcare monitoring, industrial automation, agriculture and environmental sensing. These networks generate huge amount of data at the edge devices which are usually resource constrained in power, memory and computation. Traditionally, data from sensors is sent to cloud servers for training machine learning models, but this leads to privacy issues, high communication cost, and latency. Federated Learning (FL) is a new distributed learning approach where model training happens locally on devices and only model parameters are shared instead of raw data. This concept is highly suitable for embedded sensor networks where privacy, bandwidth and energy efficiency are critical. This paper reviews the concept of federated learning applied to embedded sensor nodes, discusses system architecture, communication models, challenges, energy constraints, security aspects, and recent applications. Tables and figures are provided to show comparison with traditional centralized learning and architecture of FL-based sensor network. The paper also highlights open research problems and future directions in this area.

Keywords: Federated learning, embedded systems, sensor networks, edge AI, distributed learning, privacy preservation, IoT.  

Authors: Dheeraj S Pandey

Abstract: Energy harvesting embedded platforms have emerged as a sustainable solution for powering low-energy electronic devices, especially in IoT and remote sensing applications. These platforms utilize ambient energy sources such as solar, thermal, vibration, or radio frequency to replenish their energy reserves. However, energy availability from these sources is often unpredictable and intermittent, making efficient energy management critical. Smart scheduling techniques, which prioritize tasks based on energy availability, device importance, and system deadlines, play a vital role in optimizing performance while ensuring system longevity. This paper provides a comprehensive review of energy harvesting embedded platforms with a focus on smart scheduling strategies. It discusses recent advances in energy harvesting technologies, task scheduling algorithms, system architectures, and applications. Challenges and future research directions are also highlighted.

Keywords: Energy harvesting, Embedded platforms, Smart scheduling, IoT, Task optimization, Sustainable computing

Authors: Satyender Chauhan , Durgesh Mishra

Abstract: Generative Artificial Intelligence (AI) has rapidly evolved in recent years, enabling machines to produce text, images, audio, and video with high fidelity. Traditionally, these models rely on high-performance cloud servers due to their computational and memory demands. However, with the proliferation of Internet-of-Things (IoT) devices and embedded systems, there is an increasing need to deploy generative AI models directly on edge devices. This review explores the landscape of edge generative AI models on embedded hardware, highlighting challenges, optimization strategies, hardware architectures, and application areas. We examine model compression techniques, hardware accelerators, and energyefficient designs that allow sophisticated AI models to run on resource-constrained devices. We also discuss future directions, including federated learning, privacy-preserving AI, and ultra-low latency inference. The paper concludes with a comprehensive assessment of stateof-the-art practices and recommendations for integrating generative AI in embedded systems.

Keywords: Edge AI, Generative AI, Embedded Hardware, Model Compression, Low-Power AI, On-Device Inference  

Authors: Ramesh Sharma, N. Pradeep Kumar, Farhan Ali

Abstract: Power consumption has become a critical design concern in modern embedded systems, mobile devices, IoT nodes, and high-performance processors. With battery operated devices and dense computing platforms, efficient power management techniques are required to extend operational lifetime and reduce thermal stress. Dynamic Voltage Scaling (DVS) is one of the most effective techniques used to reduce dynamic power by adjusting supply voltage and frequency according to workload requirement. This paper presents a detailed review of Dynamic Voltage Scaling and associated power management algorithms used in real-time systems, embedded processors, and multicore architectures. Various DVS algorithms such as static, dynamic, predictive, and feedback-based methods are discussed. The paper also covers task scheduling strategies, hardware support, challenges, and real-time constraints involved in implementing DVS. Comparative analysis and practical considerations for implementing DVS in embedded firmware are also provided.

Keywords: Dynamic Voltage Scaling, Power Management, Embedded Systems, Energy Efficiency, Scheduling Algorithms, Low Power Design, DVFS, Real-Time Systems  

Authors: Gautam Pandey , Piyush Chandra , Raghuveer Singh

Abstract: Wireless Mesh Networks (WMNs) are emerging as a reliable communication backbone for distributed embedded control systems used in industrial automation, smart grids, intelligent transportation, and environmental monitoring. Unlike traditional centralized architectures, distributed control relies on multiple embedded nodes cooperating over a wireless medium to sense, compute, and actuate in real time. WMNs provide self-healing, multi-hop communication, redundancy, and scalability which are very suitable for such systems. However, challenges like latency, packet loss, synchronization, energy constraints, and security must be carefully addressed. This paper reviews the architecture, protocols, design considerations, and applications of WMNs in distributed embedded control. Various routing strategies, MAC layer issues, time synchronization methods, and reliability mechanisms are discussed. The paper also highlights advantages, limitations, and future research directions in integrating WMNs with embedded control platforms.

Keywords: Wireless Mesh Network, Distributed Control, Embedded Systems, Multi-hop Communication, Real-time Systems, Industrial Automation 

Authors: Ravinder Seth , Ankur Joshi

Abstract: Embedded systems are increasingly required to run applications across heterogeneous hardware platforms with limited resources, strict power budgets, and long deployment lifetimes. Traditional approaches depend heavily on hardware-specific toolchains and operating systems, which reduces portability and increases development effort. WebAssembly (Wasm), originally designed for safe and fast execution inside web browsers, is now emerging as a promising portable runtime for embedded applications. Its sandboxed execution model, compact binary format, near-native performance, and language-agnostic compilation support make it suitable for resource-constrained devices. This paper reviews how WebAssembly can be integrated into embedded platforms to achieve portability, modularity, and secure execution. It discusses Wasm architecture, runtime models, memory handling, toolchains, and case studies of microcontroller and IoT deployments. Challenges such as real-time behavior, memory limits, and hardware interfacing are also analyzed. The study shows that WebAssembly provides a practical path toward platform-independent embedded software design, reducing vendor lock-in and simplifying cross-device deployment.

Keywords WebAssembly, Embedded Systems, Portability, IoT, Sandbox Execution, Lightweight Runtime, Edge Computing, WASI