Embedded System Technology Research Articles

Advancements in TinyML: Applications, Limitations, and Impact on IoT Devices

Artificial Intelligence (AI) and Machine Learning (ML) have experienced rapid growth in both industry and academia. However, the current ML and AI models demand significant computing and processing power to achieve desired accuracy and results, often restricting their use to high-capability devices. With advancements in embedded system technology and the substantial development in the Internet of Things (IoT) industry, there is a growing desire to integrate ML techniques into resource-constrained embedded systems for ubiquitous intelligence. This aspiration has led to the emergence of TinyML, a specialized approach that enables the deployment of ML models on resource-constrained, power-efficient, and low-cost devices. Despite its potential, the implementation of ML on such devices presents challenges, including optimization, processing capacity, reliability, and maintenance. This article delves into the TinyML model, exploring its background, the tools that support it, and its applications in advanced technologies. By understanding these aspects, we can better appreciate how TinyML is transforming the landscape of AI and ML in embedded and IoT systems.

Implementation of Sound Direction Detection and Mixed Source Separation in Embedded Systems.

In recent years, embedded system technologies and products for sensor networks and wearable devices used for monitoring people's activities and health have become the focus of the global IT industry. In order to enhance the speech recognition capabilities of wearable devices, this article discusses the implementation of audio positioning and enhancement in embedded systems using embedded algorithms for direction detection and mixed source separation. The two algorithms are implemented using different embedded systems: direction detection developed using TI TMS320C6713 DSK and mixed source separation developed using Raspberry Pi 2. For mixed source separation, in the first experiment, the average signal-to-interference ratio (SIR) at 1 m and 2 m distances was 16.72 and 15.76, respectively. In the second experiment, when evaluated using speech recognition, the algorithm improved speech recognition accuracy to 95%.

Compact and Wearable Ventilator System for Enhanced Patient Care

Developing an innovative response to the challenges presented by the COVID-19 pandemic, our initiative strategically addresses the pressing issue of ventilator shortages and the intricacies of patient care within medical facilities. The primary focus is on the creation of a compact and wearable ventilator using embedded systems technology. Inspired by the surge in mechanical ventilator designs during the pandemic, our proposed system evolves from a simple, cost-effective device to a sophisticated solution tailored to meet the specific demands of pulmonologists and medical practitioners. The urgency in healthcare, compounded by the limited availability of ventilators, underscores the critical need for a portable and effective solution. Traditional ventilators are complicated due to challenges such as size, weight, cost, and complexity, confining their use to medical facilities and elevating the risk of secondary infections. To combatthese issues, our project seeks to design a smaller, more accessible ventilator, presenting a practical alternative for patients facing economic constraints or restricted access to medical facilities.

A Versatile Embedded Platform for Implementation of Bio Cooperative Control in Upper-Limb Neuro Motor Rehabilitation Scenario ,

This paper presents a versatile embedded platform designed for the implementation of bio-cooperative control in upper-limb neuromotor rehabilitation scenarios. With an increasing demand for effective rehabilitation techniques, particularly in cases of upper-limb impairments, there is a growing need for innovative technologies that can seamlessly integrate with existing rehabilitation protocols. The proposed platform leverages embedded systems technology to offer real-time feedback and control, facilitating personalized and interactive rehabilitation exercises. By incorporating bio- cooperative control strategies, which enable seamless collaboration between the user and the rehabilitation system, the platform aims to enhance engagement and effectiveness of rehabilitation sessions. The platform's versatility allows it to be easily customized and adapted to different rehabilitation scenarios, making it a promising tool for improving outcomes in upper-limb neuromotor rehabilitation.

Enhanced Priority-Integrated Mult winner Voting Software

Modern democracy values efficient, fair elections. This paper offers Google Cola an embedded interactive multi-winner voting method to improve democracy. Candidates and values can be entered using Python in the Colab. Basic Python algorithms and classes simplify priority candidate multi-winner elections. According to user feedback, event-driven programming modifies candidate priority enabling accurate and effective elections. These embedded system functions prioritize, rank, and aggregate votes. These mathematics facilitate fair and transparent outcome processing. This research demonstrates the embedded system's technology deployment and potential to support inclusive elections. The proposed solution helps electoral democratization by integrating collaboration with cutting-edge technologies

Detection of Malicious Threats Exploiting Clock-Gating Hardware Using Machine Learning

Embedded system technologies are increasingly being incorporated into manufacturing, smart grid, industrial control systems, and transportation systems. However, the vast majority of today’s embedded platforms lack the support of built-in security features which makes such systems highly vulnerable to a wide range of cyber-attacks. Specifically, they are vulnerable to malware injection code that targets the power distribution system of an ARM Cortex-M-based microcontroller chipset (ARM, Cambridge, UK). Through hardware exploitation of the clock-gating distribution system, an attacker is capable of disabling/activating various subsystems on the chip, compromising the reliability of the system during normal operation. This paper proposes the development of an Intrusion Detection System (IDS) capable of detecting clock-gating malware deployed on ARM Cortex-M-based embedded systems. To enhance the robustness and effectiveness of our approach, we fully implemented, tested, and compared six IDSs, each employing different methodologies. These include IDSs based on K-Nearest Classifier, Random Forest, Logistic Regression, Decision Tree, Naive Bayes, and Stochastic Gradient Descent. Each of these IDSs was designed to identify and categorize various variants of clock-gating malware deployed on the system. We have analyzed the performance of these IDSs in terms of detection accuracy against various types of clock-gating malware injection code. Power consumption data collected from the chipset during normal operation and malware code injection attacks were used for models’ training and validation. Our simulation results showed that the proposed IDSs, particularly those based on K-Nearest Classifier and Logistic Regression, were capable of achieving high detection rates, with some reaching a detection rate of 0.99. These results underscore the effectiveness of our IDSs in protecting ARM Cortex-M-based embedded systems against clock-gating malware.

Embedded System Technology Spillover Effects of Digital Economy and High-Quality Economic Development

INTRODUCTION: With the development of digital technology and computer technology, the theory of digital economy has also had far-reaching development, but at present, the digital economy is still not able to clearly define whether the digital economy is good or bad for the high-quality development of China's economy. Therefore, it is necessary to research the spillover effect of the digital economy and the high-quality development of the economy with the help of embedded system technology.OBJECTIVES: To solve the issue of the poor coupling between the digital economy and high-quality development, to raise the degree of China's digital economic development, to improve the high energy consumption in the course of China's economic high-quality development, and to improve the application level of system technology in the study of China's economic development.METHODS: The digital economy model is established using the entropy weight method; its efficiency is evaluated using embedded system technology; the spillover effect analysis of high-quality development is then conducted using the digital economy index; and lastly, the overall assessment of the spillover effect is conducted using the comprehensive evaluation results of the entropy weight method.RESULTS: Embedded system technology has a noticeable promotion effect on the development of the digital economy; although the development of the digital economy and economic high-quality development are poorly coupled, their promotion effect is more significant; embedded system technology can indirectly promote the development of economic high-quality development through the digital economy.CONCLUSION: China should vigorously develop embedded system technology to promote the application of new technology in the economy and should further standardize the market economic order to maintain the orderly development of the digital economy.

Eco-Energy Sensor Networks

This project perpetual environmentally powered sensor networks aims to develop a system for harvesting energy from the renewable environmental energy source using the embedded systems technology. Utilizing environmental energy sources holds great appeal as a power supply for low- power wireless sensor networks.This has become a major problem now a days as the proposed system involves human intervention. This project is aiming to pinpoint the best hardware selections that align with the requirements of a particular application. The primary goal is to optimize the hardware to precisely cater to the needs and demands of the given application. The primary design obstacle involves minimizing stress on storage components while maintaining a straightforward hardware and software structure. This design is a smart system that integrates streamlined, efficient hardware with robust software. This system will actively oversee the power subsystem to ensure continuous operation

Technology for SMS-based assistive device for the visually impaired

The term "tunanetra" is used to refer to someone who experiences total blindness or visual impairment. Such visual limitations result in visually impaired individuals facing difficulties in accessing information quickly and performing daily activities like walking, driving, and more. Walking is one of the crucial activities for visually impaired individuals because it is one way to explore the world and engage in daily activities. Based on this issue, an assistive device for the visually impaired was designed using embedded system technology. In 2022, Serly Juliana Taneo, Jonshon Tarigan, Frederika Rambu Ngana, and Andreas Ch. Louk developed a mobility aid device for individuals with visual impairments using ultrasonic sensors for distance detection and Arduino as the microcontroller. However, the device primarily focused on mobility, and there is a need to add new features, such as emergency information using SMS technology that can send messages with the press of a button. The research results indicate that the ultrasonic sensor successfully triggers vibrations within a range of 1-100 cm, and the button can send emergency notifications via SMS when pressed. Therefore, it can be concluded that all connected components can function as intended. By combining SMS technology and ultrasonic sensors, this assistive device is expected to enhance the safety and independence of individuals with visual impairments as they navigate their surroundings.

Efficient Algebraic Method for Testing the Invertibility of Finite State Machines

The emergence of new embedded system technologies, such as IoT, requires the design of new lightweight cryptosystems to meet different hardware restrictions. In this context, the concept of Finite State Machines (FSMs) can offer a robust solution when using cryptosystems based on finite automata, known as FAPKC (Finite Automaton Public Key Cryptosystems), introduced by Renji Tao. These cryptosystems have been proposed as alternatives to traditional public key cryptosystems, such as RSA. They are based on composing two private keys, which are two FSMs M1 and M2 with the property of invertibility with finite delay to obtain the composed FSM M=M1oM2, which is the public key. The invert process (factorizing) is hard to compute. Unfortunately, these cryptosystems have not really been adopted in real-world applications, and this is mainly due to the lack of profound studies on the FAPKC key space and a random generator program. In this paper, we first introduce an efficient algebraic method based on the notion of a testing table to compute the delay of invertibility of an FSM. Then, we carry out a statistical study on the number of invertible FSMs with finite delay by varying the number of states as well as the number of output symbols. This allows us to estimate the landscape of the space of invertible FSMs, which is considered a first step toward the design of a random generator.

An Analysis of : Embedded Systems in Embedded Processors Knack

The mechanisms via way of means of which software program interacts with the bodily international are converting rapidly. Today’s fashion is “smart” sensors and drives with microprocessors, community interfaces and software program that permit far flung get entry to to sensor records and far flung unit activation. There is likewise the Internet of Things (IoT), Industry 4.0, Industrial Internet, Machine to Machine, Internet of Everything, Smart Planet, TSensors (trillions of sensors) or Fog (similar, however towards the cloud). Earth is an expression of era that deeply connects our bodily and informational worlds. In the IoT international, the interfaces among those worlds are stimulated and derived from statistics era, specially net era. Our recognition is on interacting with the bodily surroundings wherein software program and hardware operate. This calls for a unique modeling of the time dynamics of the software program and networks and a clean specification of the parallel nature of the application. The truth that implementation era has now no longer but reached this factor need to now no longer educate a incorrect technonical approach. All need to learn design and modeling and enrich them with a critical reflection on what it is. Today’s embedded systems technology should be presented in a neutral way, not as a collection of facts and tricks, as in many of the recent trends in, but as a cornerstone to a better design experience.

Blockchain Enabled Anonymous Privacy-Preserving Authentication Scheme for Internet of Health Things.

The Internet of Health Things (IoHT) has emerged as an attractive networking paradigm in wireless communications, integrated devices and embedded system technologies. In the IoHT, real-time health data are collected through smart healthcare sensors and, in recent years, the IoHT has started to have an important role in the Internet of Things technology. Although the IoHT provides comfort in health monitoring, it also imposes security challenges in maintaining patient data confidentiality and privacy. To overcome such security issues, in this paper, a novel blockchain-based privacy-preserving authentication scheme is proposed as an approach for achieving efficient authentication of the patient without the involvement of a trusted entity. Moreover, a secure handover authentication mechanism that ensures avoiding the patient re-authentication in multi-doctor communication scenarios and revoking the possible malicious misbehavior of medical professionals in the IoHT communication with the patient is developed. The performance of the proposed authentication and handover scheme is analyzed concerning the existing state-of-the-art authentication schemes. The results of the performance analyses reveal that the proposed authentication scheme is resistant to different types of security attacks. Moreover, the results of analyses show that the proposed authentication scheme outperforms similar state-of-the-art authentication schemes in terms of having lower computational, communication and storage costs. Therefore, the novel authentication and handover scheme has proven practical applicability and represents a valuable contribution to improving the security of communication in IoHT networks.

Design of Personal Health Monitoring Devices for Early Detection of Silent Hypoxia

Silent hypoxia in Covid-19 patients and symptoms of severe hypoxemia require appropriate treatment. These cases often appear asymptomatic but risk fatal to life-threatening. One of the recommended devices is pulse oximetry. Embedded systems technologies and the Internet of Things (IoT) can develop low-cost personal health monitoring devices. This study developed a pulse oximetry prototype integrated with a digital temperature sensor and equipped with the interpretation results of both "normal" and "hypoxic" conditions. It is called OxyTemp. IoT technologies monitor user conditions remotely using the Blynk application via mobile phones. This study used Research & Development with the Reverse engineering method. The OxyTemp has Different types of prototype testing are physical and functional inspection, electrical safety testing, and performance testing of each parameter using an appropriate calibrator. The working method refers to SK Direktur Jenderal Pelayanan Kesehatan Tahun 2018 No. 041-18 on Pulse Oximeter Testing Working Methods.

Intelligent Application of Artificial Intelligence Internet of Things Technology in the Economic and Legal Fields

In today’s globalized situation, people on the one hand enjoy the great convenience brought by the Internet and artificial intelligence Internet of Things (IoT) technology, and, on the other hand, they are also inevitably subject to a series of harms brought by network technology. Internet economic crime is a new type of crime based on Internet technology. Criminals use Internet technology to conduct illegal visits and Trojan horse program attacks, steal user information, and defraud victims of money. This has resulted in the people’s personal and property safety and social harmony and stability. Strictly cracking down on cyber economic crimes in accordance with the law is of great significance to safeguarding the interests of the people and maintaining social stability. However, as the methods and forms of cyber economic crimes emerge endlessly, it is very important to collect intelligence information on such crimes. This paper proposes using the sensor technology, embedded system technology, radio frequency automatic identification technology, and cloud computing technology in artificial intelligence Internet of Things technology to design and build a data-mining-based network economic crime intelligent information aggregation collection system to realize network economic crime intelligence of aggregation and analyze and help combat cyber economic crimes. This article takes cyber economic crime cases in various cities in our province as an example, selects 9 cyber economic criminals’ intelligence information as sample data, and tests and applies the designed cyber economic crime intelligence information system. The final results show that the numbers of cyber economic crime cases in four cities A, B, C, and D in four provinces are roughly the same, but city A has the largest number; the minimum confidence of the 9 criminals is above 0.60, indicating that the economic crimes of cyber economic criminals are related to their academic background and family status and criminal history are related to a certain extent; illegal fund-raising fraud and online credit card fraud account for the largest proportion of the four cities and are currently the main forms of online economic crime.

An Overview of Machine Learning within Embedded and Mobile Devices-Optimizations and Applications.

Embedded systems technology is undergoing a phase of transformation owing to the novel advancements in computer architecture and the breakthroughs in machine learning applications. The areas of applications of embedded machine learning (EML) include accurate computer vision schemes, reliable speech recognition, innovative healthcare, robotics, and more. However, there exists a critical drawback in the efficient implementation of ML algorithms targeting embedded applications. Machine learning algorithms are generally computationally and memory intensive, making them unsuitable for resource-constrained environments such as embedded and mobile devices. In order to efficiently implement these compute and memory-intensive algorithms within the embedded and mobile computing space, innovative optimization techniques are required at the algorithm and hardware levels. To this end, this survey aims at exploring current research trends within this circumference. First, we present a brief overview of compute intensive machine learning algorithms such as hidden Markov models (HMM), k-nearest neighbors (k-NNs), support vector machines (SVMs), Gaussian mixture models (GMMs), and deep neural networks (DNNs). Furthermore, we consider different optimization techniques currently adopted to squeeze these computational and memory-intensive algorithms within resource-limited embedded and mobile environments. Additionally, we discuss the implementation of these algorithms in microcontroller units, mobile devices, and hardware accelerators. Conclusively, we give a comprehensive overview of key application areas of EML technology, point out key research directions and highlight key take-away lessons for future research exploration in the embedded machine learning domain.

The uncoupled microbial fed-batch fermentation optimization based on state-dependent switched system

In the actual microbial fermentation process, excessive or insufficient substrate can produce inhibitory effects on cells growth. The artificial substrate feeding rules by past experiences have great blindness to keep substrate concentration in a given appropriate range. This paper considers that alkali feed depends on pH value of the solution and glycerol feed depends on glycerol concentration of the solution in the uncoupled microbial fed-batch fermentation process, and establishes a state-dependent switched system in which the flow rates of glycerol and alkali, the number of mode switches, the mode sequence and the switching times are prior unknown. To maximize the yield of target product 1,3-Propanediol (1,3-PD), we formulate a switching optimal control problem with the flow rates of glycerol and alkali, the number of mode switches, the mode sequence and the switching times as decision variables, which is a mixed-integer dynamic programming problem. For solving the mixed-integer dynamic programming problem, the control parametrization technique, the time scaling transformation and the embedded system technology are used to obtain an approximate parameter optimization problem. By using a parallel optimization algorithm, we obtain the optimal control strategies. Under the obtained optimal control strategies, the 1,3-PD yield at the terminal time is increased significantly compared with the previous results.

Embedded systems technologies applied to environmental impacts assessment on forest firefight

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Smart Chicken Farming: Monitoring System for Temperature, Ammonia Levels, Feed in Chicken Farms

In this study, embedded system technology was implemented in the supervision system of chicken farms. This system works by utilizing sensors that are used to collect data on temperatures, ammonia levels, chicken food in the chicken coop. The method used in this study consisted of three stages. The first stage is a literature study on problems that often occur in chicken farms. The second step is to make observations directly to the farm to get more information. Then proceed with the implementation and testing. The research data were collected through observations and interviews with breeders on chicken farms, Bogor district. The results of the study show that the system can monitor ammonia levels, chicken food weight, and room temperature. The farmer can easily monitor the condition of chicken farms and get SMS notifications on situations that need to be dealt with immediately. The research data were collected through observations and interviews with breeders on chicken farms, Bogor district. The results of the study show that the system can monitor ammonia levels, chicken food weight, and room temperature.

A Portable Device for Wound Healing with Self-charging Capability

Herein, a portable device for wound healing with self-charging capability has been proposed by utilizing embedded system technology with an electromagnetic energy harvester. With the storing capability, the harvester can generate electricity from human vibration. By enhancing the coil turns and speed of the magnet, the generation rate of the harvester can be increased. The vacuum environment can be easily established by a vacuum pump. According to the negative pressure sensor's data, the environment can be easily stabilized by applying Pulse Width Modulation (PWM) signal to the pump driver. By using adhesive drape, the wound surface can be easily fitted with the fluid container. The device can be used at indoor and outdoor environment uninterruptedly.

Security of RPL Based 6LoWPAN Networks in the Internet of Things: A Review

Internet of Things (IoT) is one of the fastest emerging networking paradigms enabling a large number of applications for the benefit of mankind. Advancements in embedded system technology and compressed IPv6 have enabled the support of IP stack in resource constrained heterogeneous smart devices. However, global connectivity and resource constrained characteristics of smart devices have exposed them to different insider and outsider attacks, which put users' security and privacy at risk. Various risks associated with IoT slow down its growth and become an obstruction in the worldwide adoption of its applications. In RFC 6550, the IPv6 Routing Protocol for Low Power and Lossy Network (RPL) is specified by IETF's ROLL working group for facilitating efficient routing in 6LoWPAN networks, while considering its limitations. Due to resource constrained nature of nodes in the IoT, RPL is vulnerable to many attacks that consume the node's resources and degrade the network's performance. In this paper, we present a study on various attacks and their existing defense solutions, particularly to RPL. Open research issues, challenges, and future directions specific to RPL security are also discussed. A taxonomy of RPL attacks, considering the essential attributes like resources, topology, and traffic, is shown for better understanding. In addition, a study of existing cross-layered and RPL specific network layer based defense solutions suggested in the literature is also carried out.