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Embedded Ethernet and Controller Area Network (CAN) protocol can be used in control network to achieve hard real-time communication. For embedded Ethernet protocol, Carrier Sense Multiple Access with Collision Detection (CSMA/CD) is the... more
Embedded Ethernet and Controller Area Network (CAN) protocol can be used in control network to achieve hard real-time communication. For embedded Ethernet protocol, Carrier Sense Multiple Access with Collision Detection (CSMA/CD) is the media access control (MAC) used to control data transmission between nodes in network. Back-off algorithm in CSMA/CD is used to handle packet collisions and retransmission. For CAN protocol that developed for automotive application, it has priority arbitration to handle collisions and retransmission. In this paper, embedded Ethernet network models and CAN network models are developed and simulated in MATLAB Simulink software. Several back-off algorithms, which are Binary Exponential Backoff (BEB), Linear Back-off Algorithm, Exponential-Linear back-off Algorithm and Logarithm Back-off Algorithm are proposed and implemented into Embedded Ethernet network model to evaluate the performance. Both embedded Ethernet and CAN network models are extended to 3, 10 and 15 nodes to evaluate performance at different network condition. The performance criteria evaluated and discussed are average delay and jitter of packets. The results show that in network with high number of nodes, Linear Back-off Algorithm and Exponential-Linear back-off Algorithm shows improvement in packets delay, 61% and jitter, 83% compared to standard algorithm, BEB. For CAN network, the packet jitter is relatively low, 0.293 ms.
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The unprecedented outbreak of novel coronavirus 2019 (COVID-19) globally has a huge impact to our daily life in numerous ways. To effectively minimize the spread of the virus, early symptom detection is crucial, especially in closed... more
The unprecedented outbreak of novel coronavirus 2019 (COVID-19) globally has a huge impact to our daily life in numerous ways. To effectively minimize the spread of the virus, early symptom detection is crucial, especially in closed environment with high human traffic areas which post higher chances of human-to-human transmission. Body temperature measurement has been identified among the vital monitoring parameters. However, current available temperature monitoring mechanism is costly, limited to single individual and limited to locally without integrating to cloud and database. This led to difficulty in effective surveillance for suspicious COVID cases. Hence, the purpose of this paper is to introduce an end-to-end Internet of Things-enabled application for thermal monitoring as an early signal detection and screening method. This work integrates Raspberry Pi, thermal sensor, LCD display, buzzer, and LED light with Raspbian and Restful API for device-to-cloud communication. The sy...
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Deep reinforcement learning (DRL) which involved reinforcement learning and artificial neural network allows agents to take the best possible actions to achieve goals. Spiking Neural Network (SNN) faced difficulty in training due to the... more
Deep reinforcement learning (DRL) which involved reinforcement learning and artificial neural network allows agents to take the best possible actions to achieve goals. Spiking Neural Network (SNN) faced difficulty in training due to the non-differentiable spike function of spike neuron. In order to overcome the difficulty, Deep Q network (DQN) and Deep Q learning with normalized advantage function (NAF) are proposed to interact with a custom environment. DQN is applied for discrete action space whereas NAF is implemented for continuous action space. The model is trained and tested to validate its performance in order to balance the firing rate of excitatory and inhibitory population of spike neuron by using both algorithms. Training results showed both agents able to explore in the custom environment with OpenAI Gym framework. The trained model for both algorithms capable to balance the firing rate of excitatory and inhibitory of the spike neuron. NAF achieved 0.80% of the average p...
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Abstract : Brain Computer Interface (BCI) is a new feature of human-machine interaction for a direct communication channel from the brain. It involves the extraction of information from brain activity and translates it into system... more
Abstract : Brain Computer Interface (BCI) is a new feature of human-machine interaction for a direct communication channel from the brain. It involves the extraction of information from brain activity and translates it into system commands using feature extraction and classification algorithms. The study uses signals previously recorded in the BCI lab. Feature selection and classification were based on the Neural Network (NN), Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA). The results of classification show that LDA classifier recorded the highest accuracy in 3 and 4-class of movement compared with SVM and NN classifiers. LDA classified the 4-class of movements at central channel and single channel with the average accuracy of 43.75% and 42%. Further, LDA performed better result in 3-class of movement, with an average accuracy 62%. The highest accuracy for bandpower performed by LDA classifier with average accuracy 41.75 % at beta band.
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The advent of internet enabled small form factor computational devices have already revolutionized the way we fetch information, envision intelligent systems by inferencing real-time analytics from these IoT devices. The current trend is... more
The advent of internet enabled small form factor computational devices have already revolutionized the way we fetch information, envision intelligent systems by inferencing real-time analytics from these IoT devices. The current trend is focused towards enabling IoT edge gateways as intermediary computational resources contrary to the cloud model that performs all the heavy lifting in the cloud. It is estimated that billions of IoT devices will be deployed by year 2020, however, very little to no information is present on ease of device provisioning. Similarly, the IoT Edge based vertical markets concepts has begun to surface, however, very little information is available that discusses the merits and demerits of this newly envisioned network architecture. This paper aims to implement a Health-care domain scenario by provisioning and connecting real-time device data from simulated as well as emulated virtual IoT devices on industry leading IoT platforms. The results provide a deeper understanding of system performance by evaluating network latencies with increased payloads which further signifies the role and need for deploying Edge IoT gateways within the network. Device provisioning, service profiling and the ease of group resource management is also presented which helps to build larger scalable networks on these IoT platforms.
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The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction.... more
The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revolution, aims to combine renewable energy and Internet technology to promote the large-scale use and sharing of distributed renewable energy as well as the integration of multiple complex network systems, such as electricity, transportation, and natural gas. This novel technology enables power networks to save energy. However, multienergy synchronization optimization poses a significant problem. As a solution, this study proposed an optimized approach based on the concept of layered control–collaborate optimization. The proposed method allows the distributed device to plan the heat, cold, gas, and electricity in the regional system in the most efficient way possible. Moreover, the proposed...
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Energy conservation and optimization remains the top researched field for wireless sensor networks, which is one of a subsets and the underlying communication medium for Internet of Things (IoT) devices. These constrained IoT devices are... more
Energy conservation and optimization remains the top researched field for wireless sensor networks, which is one of a subsets and the underlying communication medium for Internet of Things (IoT) devices. These constrained IoT devices are mostly battery operated and therefore requires robust and optimized algorithms to improve resources utilization which inherently increases the life-span for these devices without compromising Quality of Service (QoS). The communication radios on these nodes are the most power hogging components. Therefore, a major focus has always been on MAC and cross-layer protocols to optimize the duty cycle of radios for the conservation of energy. This paper presents a unique scheme for dynamically adjusting the duty cycle of nodes based on the arrival of incoming infrequent source node sensor data over which eliminates the need for frequent periodic channel assessment for network activity. The proposed scheme also makes use of ultra-low wakeUp receivers on the receiver nodes to further aid the node in energy conservation. In this paper, we describe the details of our design scheme, implementation and evaluation details in Contiki OS and Cooja simulator. The results are micro-benchmarked with ContikiMAC and X-MAC protocols, and an improvement in radio duty cycle is reported for lighter network traffic.
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The COVID-19 virus exhibits pneumonia-like symptoms, including fever, cough, and shortness of breath, and may be fatal. Many COVID-19 contraction experiments require comprehensive clinical procedures at medical facilities. Clinical... more
The COVID-19 virus exhibits pneumonia-like symptoms, including fever, cough, and shortness of breath, and may be fatal. Many COVID-19 contraction experiments require comprehensive clinical procedures at medical facilities. Clinical studies help to make a correct diagnosis of COVID-19, where the disease has already spread to the organs in most cases. Prompt and early diagnosis is indispensable for providing patients with the possibility of early clinical diagnosis and slowing down the disease spread. Therefore, clinical investigations in patients with COVID-19 have revealed distinct patterns of breathing relative to other diseases such as flu and cold, which are worth investigating. Current supervised Machine Learning (ML) based techniques mostly investigate clinical reports such as X-Rays and Computerized Tomography (CT) for disease detection. This strategy relies on a larger clinical dataset and does not focus on early symptom identification. Towards this end, an innovative hybrid unsupervised ML technique is introduced to uncover the probability of COVID-19 occurrence based on the breathing patterns and commonly reported symptoms, fever, and cough. Specifically, various metrics, including body temperature, breathing and cough patterns, and physical activity, were considered in this study. Finally, a lightweight ML algorithm based on the K-Means and Isolation Forest technique was implemented on relatively small data including 40 individuals. The proposed technique shows an outlier detection with an accuracy of 89%, on average. © 2021 Tech Science Press. All rights reserved.
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The state-of-the-art robust H∞ linear parameter-varying controller is designed for wide speed operating range for non-linear mathematical model of permanent magnet synchronous machines (PMSM) in d-q reference frame for fully electric... more
The state-of-the-art robust H∞ linear parameter-varying controller is designed for wide speed operating range for non-linear mathematical model of permanent magnet synchronous machines (PMSM) in d-q reference frame for fully electric vehicle. This study propose polytopic approach using rotor speed as scheduling variable to reformulate mathematical model of PMSM into linear parameter varying (LPV) form. The weights were optimized for sensitivity and complementary sensitivity function. The simulation results illustrate fast tracking and enhanced performance of the proposed control technique over wide range of rotor speed. Moreover, as part of this work, the results of H∞ linear parameter varying controller is validated by comparing it with linear quadratic integrator and proportional integral derivative (PID) control techniques to show the effectiveness of the proposed control technique.
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The highly efficient Interior Permanent Magnet Synchronous Motor (IPMSM) is ubiquitous choice in Electric Vehicles (EVs) for today’s automotive industry. IPMSM control requires accurate knowledge of an immeasurable critical Permanent... more
The highly efficient Interior Permanent Magnet Synchronous Motor (IPMSM) is ubiquitous choice in Electric Vehicles (EVs) for today’s automotive industry. IPMSM control requires accurate knowledge of an immeasurable critical Permanent Magnet (PM) flux linkage parameter. The PM flux linkage is highly influenced by operating temperature which results in torque derating and hence power loss, unable to meet road loads and reduced life span of electrified powertrain in EVs. In this paper, novel virtual sensing scheme for estimating PM flux linkage through measured stator currents is designed for an IPMSM centric electrified powertrain. The proposed design is based on a Uniform Robust Exact Differentiator (URED) centric Super Twisting Algorithm (STA), which ensures robustness and finite-time convergence of the time derivative of the quadrature axis stator current of IPMSM. Moreover, URED is able to eliminate chattering without sacrificing robustness and precision. The proposed design detec...
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This dataset reports the discharge profiles of 4 battery chemistries under IEEE 802.15.4 radio load profiles. The batteries were independently subjected to a five-step method to record the discharge characteristics. These discharge... more
This dataset reports the discharge profiles of 4 battery chemistries under IEEE 802.15.4 radio load profiles. The batteries were independently subjected to a five-step method to record the discharge characteristics. These discharge currents, their effect on battery capacity, and surface temperature may affect the overall battery lifetime, which was the major aim to discover. The following batteries were used in these experiements <b>Tag</b> <b>Manufacturer</b> <b>Model</b> <b>Battery Chemistry</b> <b>Capacity (mAh)</b> <b>Nominal Voltage</b> <b>C-Rate</b> Batt1 Powerizer MH-AAA1000APZ Nickel-Metal Hydride (Ni-mh) 1000 1.2 V 1C Batt2 Data Power Technology DTP603450 Polymer Lithium-Ion (LiPo) 1000 3.7V 1C Batt3 Panasonic UF553443ZU Lithium-Ion (Li-ion) 1000 3.6V 1C Batt4 Energizer LR-6 Alkaline (Zinc, Magnesium Dioxide) Variable, load dependent 1.5V 2C The five step methodlogy proceeded as: Pre-conditi...
Wireless sensor networks (WSN) are commonly used in remote environments for monitoring and sensing. These devices are typically powered by batteries, the performance of which varies depending on environmental (such as temperature and... more
Wireless sensor networks (WSN) are commonly used in remote environments for monitoring and sensing. These devices are typically powered by batteries, the performance of which varies depending on environmental (such as temperature and humidity) as well as operational conditions (discharge rate and state-of-charge, SOC). As a result, assessing their technical viability for WSN applications requires performance evaluation based on the aforementioned stimuli. This paper proposes an efficient method for examining battery performance parameters such as capacity, open-circuit voltage (OCV) and SOC. Four battery types (lithium-ion, lithium-polymer, nickel-metal hydride and alkaline) were subjected to IEEE 802.15.4 protocol-based discharge rates to record the discharge characteristics. Furthermore, the combined effect of discharge rates on battery surface temperature and OCV variations was investigated. Shorter relaxation times (4–8 h) were observed in lithium-based batteries, resulting in f...
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The Internet of Things (IoT) is an extensive network of heterogeneous devices that provides an array of innovative applications and services. IoT networks enable the integration of data and services to seamlessly interconnect the cyber... more
The Internet of Things (IoT) is an extensive network of heterogeneous devices that provides an array of innovative applications and services. IoT networks enable the integration of data and services to seamlessly interconnect the cyber and physical systems. However, the heterogeneity of devices, underlying technologies and lack of standardization pose critical challenges in this domain. On account of these challenges, this research article aims to provide a comprehensive overview of the enabling technologies and standards that build up the IoT technology stack. First, a layered architecture approach is presented where the state-of-the-art research and open challenges are discussed at every layer. Next, this research article focuses on the role of middleware platforms in IoT application development and integration. Furthermore, this article addresses the open challenges and provides comprehensive steps towards IoT stack optimization. Finally, the interfacing of Fog/Edge Networks to I...
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Internet of things (IoT) technology is growing exponentially in almost every sphere of life. IoT offers several innovation capabilities and features, but they are also prone to security vulnerabilities and risks. These vulnerabilities... more
Internet of things (IoT) technology is growing exponentially in almost every sphere of life. IoT offers several innovation capabilities and features, but they are also prone to security vulnerabilities and risks. These vulnerabilities must be studied to protect these technologies from being exploited by others. Cryptography techniques and approaches are commonly used to address and deal with security vulnerabilities. In general, the message queuing telemetry transport (MQTT) is an application layer protocol vulnerable to various known and unknown security issues. One possible solution is to introduce an encryption algorithm into the MQTT communication protocol for secure transmission. This study aims to solve the security problem of IoT traffic by using a secure and lightweight communication proxy. The strategy behind this communication broker acts as a network gateway providing secure transaction keys to all IoT nodes in the network. This task uses a java servlet and elliptic curve...
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In the past two decades the interoperability of Information Systems counted from the main key feature of successful e-Government projects. While information systems and technologies are being developed and enhanced, many discussions on... more
In the past two decades the interoperability of Information Systems counted from the main key feature of successful e-Government projects. While information systems and technologies are being developed and enhanced, many discussions on their success have been accomplished by scholars and researchers. Moreover, they found that achieving of IS interoperability between different institutions is a complex task and influenced by different aspects. As a part of these aspects the semantic and technical factors considered from the main issues related to interoperability. This study investigates the semantic and technical factors that affect the level of interoperability with focusing on interoperability of IS as a key concept to achieve the successful implementation of interoperability in the public sector. In order to explore the variables of the study and its relations, a variety of published literatures on the scope of the study was critically reviewed. Furthermore, data was collected us...
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Embedded system testing involves testing an integration of software and hardware. It is increasingly difficult to evaluate the functionality of each module within a short time because of the increasing number of tests required. In this... more
Embedded system testing involves testing an integration of software and hardware. It is increasingly difficult to evaluate the functionality of each module within a short time because of the increasing number of tests required. In this paper, a novel stepwise methodology involving the use of an automated compilation test system (ACTS) is proposed, to improve the quality of testing and optimize the testing time using automation. Using the proposed method, the testing coverage can be maximized, while minimizing the manual work and testing time required. This ACTS was used to automate the test code compilation and execution for different hardware modules. The proposed method significantly saved the testing time by approximately 56.42%, compared to the existing method, while ensuring quality testing performance.
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This release features the dataset recorded using our prototype hardware device (contact-based) that collects accelerometer and temperature readings to investigate breathing patterns, personal activity and cough patterns. As fever and... more
This release features the dataset recorded using our prototype hardware device (contact-based) that collects accelerometer and temperature readings to investigate breathing patterns, personal activity and cough patterns. As fever and cough are considered as two of the most common symptoms for COVID-19, our aim was to focus on these physiological features. In addition, research also states that all COVID-19 contractions showed elevated breathing patterns in patients, that could be easily identifiable from Eupnea state. Therefore, in this research project, we aimed at:<br> 1. Designing a prototype chest-worn device to measure dynamic chest movements (to record breathing and cough patterns)<br> 2. Detect different activity patterns<br> 3. Record temperature variations during idle and active stage<br> 4. Using unsupervised machine learning algorithm to detect anomalies by creating a composite score for (breathing and cough patterns as well as temperature). This release also features some code examples that were used for data pre-processing, feature identification and anomaly detection using (K-means and DBSCAN algorithms). It is important to note that this dataset should be considered and further investigated for preliminary exploratory analysis. The data was collected from healthy adults (that did not undergo COVID-19 clinical screening tests). Therefore, it must be clearly identified that this dataset DOES NOT represent positive COVID-19 contractions.
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This dataset is based on the experimental study to monitor Covid-19 symptoms such as fever and dry cough and extract features to detect anomalies. The data is generated from a chest worn device where accelerometer values model the... more
This dataset is based on the experimental study to monitor Covid-19 symptoms such as fever and dry cough and extract features to detect anomalies. The data is generated from a chest worn device where accelerometer values model the behavior of cough patterns, whereas digital infrared thermometer readings are also recorded and timestamped for each set of observations.
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This paper presents the process of developing a controller for a robotic arm that is built through the Internet of Things (IoT). The direction of the robotic arm can be monitored and controlled using internet facilities. The Raspberry Pi... more
This paper presents the process of developing a controller for a robotic arm that is built through the Internet of Things (IoT). The direction of the robotic arm can be monitored and controlled using internet facilities. The Raspberry Pi board is utilized in this project for the robotic arm controller as well as the web server system. The robotic arm comprises four servo motors and each of the servo motors is assigned with a single pulse width modulation (PWM) output that can be individually controlled. The controller system is implemented on Raspberry Pi board using Python 2.7 programming language. Node-Red is used as a web server in this project to communicate with the web browser through TCP/HTTP. Hence, this allows the user to access the web browser using computer or smartphones. In addition, it enables the monitoring and controlling of the robotic arm direction as well as performing pick and place task similar to the manufacturing industry. The results of this study are verifie...
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This paper proposes an alternative control communication system through CANopen application which will be used for controlling an underactuated anthromorphic fingers. It is anticipated that the CANopen network can be developed easily and... more
This paper proposes an alternative control communication system through CANopen application which will be used for controlling an underactuated anthromorphic fingers. It is anticipated that the CANopen network can be developed easily and reliable to integrate with Bristol Elumotion Robot Hand (BERUL). The real-time network has to incorporate into dSPACE and a well-known Matlab Simulink-based controller prototyping system. Experimental result has proved that the CANopen is reliable to be implemented for underactuated anthromorphic fingers.
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ABSTRACT An approach for cheap and deterministic control communication using Ethernet real-time control communication is presented. Field-programmable gate array (FPGA) technology, i.e Xilinx XC3S500E from the Spartan-3E family, is used... more
ABSTRACT An approach for cheap and deterministic control communication using Ethernet real-time control communication is presented. Field-programmable gate array (FPGA) technology, i.e Xilinx XC3S500E from the Spartan-3E family, is used to implement the Ethernet communication strategy. The unit is defined in Verilog using Xilinx ISE 11.1 software tools. Data packages are sent at well defined times to avoid collisions. Collisions mainly occur due to jitter of the transmitter system, so that arbitration (similar to CANopen) is necessary. The Binary Exponential Backoff (BEB) scheme is used. This paper analyzes and investigates how the backoff time affects the performance of the Carrier Sense Multiple Access protocol with Collision Detection (CSMA/CD) in a basic Media Access Controller (MAC), in terms of data arrival characteristics, i.e jitter and delay. We propose to assign different minimal backoff times for each of the CSMA/CD controller units to minimize packet collisions. The proposed hardware design shows the advantage of our approach over a standard CSMA/CD setting.
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Deterministic control communication is a backbone of many novel robotic complex systems, e.g HUBO uses CAN. The aim of this paper, in contrast, is to develop an approach for cheap and deterministic control communication using Ethernet... more
Deterministic control communication is a backbone of many novel robotic complex systems, e.g HUBO uses CAN. The aim of this paper, in contrast, is to develop an approach for cheap and deterministic control communication using Ethernet real-time control communication. A half-duplex Ethernet network populated with a small/medium number of Media Access Controllers (MACs) is used for timed real-time communication. Matlab and Field-programmable gate array (FPGA) technology, i.e Xilinx XC3S500E from the Spartan-3E family, are used to simulate and implement the Ethernet communication strategy. The FPGA units are programmed in Verilog using Xilinx ISE 11.1 software tools. For communication, a time-triggered approach is used, i.e a synchronization signal triggers the sending of data from each Ethernet data transmitting unit. Moreover, data packages are sent at well defined times after each trigger instant to reduce collisions. Collisions mainly occur due to jitter of the transmitter system, so that arbitration (similar to CANopen) is necessary. A Linear Backoff scheme is used in comparison to the Binary Exponential backoff scheme. This paper analyzes and investigates how the backoff scheme affects the performance of the Carrier Sense Multiple Access protocol with Collision Detection (CSMA/CD) in a basic MAC, in terms of data arrival characteristics, i.e jitter and delay for deterministic control communication. We propose to assign different minimal back-off times for each of the CSMA/CD controller units and FPGA boards to minimize packet collisions.
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Over the last decade, the Internet of Things (IoT) domain has grown dramatically, from ultra-low-power hardware design to cloud-based solutions, and now, with the rise of 5G technology, a new horizon for edge computing on IoT devices will... more
Over the last decade, the Internet of Things (IoT) domain has grown dramatically, from ultra-low-power hardware design to cloud-based solutions, and now, with the rise of 5G technology, a new horizon for edge computing on IoT devices will be introduced. A wide range of communication technologies has steadily evolved in recent years, representing a diverse range of domain areas and communication specifications. Because of the heterogeneity of technology and interconnectivity, the true realisation of the IoT ecosystem is currently hampered by multiple dynamic integration challenges. In this context, several emerging IoT domains necessitate a complete re-modeling, design, and standardisation from the ground up in order to achieve seamless IoT ecosystem integration. The Internet of Nano-Things (IoNT), Internet of Space-Things (IoST), Internet of Underwater-Things (IoUT) and Social Internet of Things (SIoT) are investigated in this paper with a broad future scope based on their integrati...
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Controller Area Network (CAN) is a network that allows communication between ECUs in a vehicle by introducing a cheaper and light-weight communication medium. CAN is an asynchronous protocol yet provides efficient synchronous mechanism.... more
Controller Area Network (CAN) is a network that allows communication between ECUs in a vehicle by introducing a cheaper and light-weight communication medium. CAN is an asynchronous protocol yet provides efficient synchronous mechanism. Therefore, it is crucial to make sure the message transmission in CAN bus is accurate and does not miss its deadline. Local Interconnect Network (LIN) bus, is widely adopted as an alternative and additive bus protocol that has been used to complement CAN. In this project, the objective is to investigate the performance of the CAN signal generated from CAN simulator - CANOE, with and without the integration LIN. Moreover, this paper aims to observe the difference between these two different methods of signal transmission. As to create an experiment environment with the CAN and LIN simulation, the KWP Diagnostic Tester is created. Based on the established model, 4 cases have been introduced to create 4 different test environments, to showcase the diffe...
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Clear Channel Assessment (CCA) is an integral component of CSMA based Medium Access Control (MAC) protocols employing channel sensing during transmission. The channel sensing mechanism is a cross-layer scheme where CCA operates at the PHY... more
Clear Channel Assessment (CCA) is an integral component of CSMA based Medium Access Control (MAC) protocols employing channel sensing during transmission. The channel sensing mechanism is a cross-layer scheme where CCA operates at the PHY layer, used on the transmitter and receiver side, impacting the MAC layer, including the node's energy consumption and overall throughput. This paper evaluates IEEE 802.15.4 standard-based MAC protocols for various traffic conditions. It proposes an adaptive CCA (A-CCA) timing mechanism to improve node energy consumption by reducing node time in false wakeups and idle-listening modes. ACCA helps transmitters to adjust their radio powers in high traffic and interference environments above the noise floor, allowing the receiver to monitor the sender signal and adjust its wakeup period accordingly. The proposed scheme was evaluated using Cooja Simulator as well as CC2420 based platforms to report improved node lifetime and reduce false wakeups und...
The complexity of an embedded system is directly proportional to the requirements of industrial applications. Various embedded operating system (OS) approaches had been built to fulfil the requirements. This review aims to systematically... more
The complexity of an embedded system is directly proportional to the requirements of industrial applications. Various embedded operating system (OS) approaches had been built to fulfil the requirements. This review aims to systematically address the similarities and differences of the embedded OS solutions and analyse the factors that will influence decision-making when choosing what solution to use in the applications. This paper reviews three standard solutions; super loop, cooperative, and real-time operating system (RTOS). These are commonly used in industrial applications. By grouping the tasks in the foreground and background execution region, the concept and working principle of each of them are reviewed. The unique feature of RTOS in the context of task switching was used to define the deterministic characteristic of meeting the deadlines. The importance and performance of this characteristic is addressed and compared among various solutions in this paper. Subsequently, this...
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This paper presents a controllable robotic arm via the use of the Internet of Things (IoT). A nurse could control the robotic arm in a hospital to assist a doctor during a surgery and take care of the patient with the picking and placing... more
This paper presents a controllable robotic arm via the use of the Internet of Things (IoT). A nurse could control the robotic arm in a hospital to assist a doctor during a surgery and take care of the patient with the picking and placing tasks using the robotic arm. In this system, a smart phone will be used to control the robotic arm. An accelerometer and a gyroscope are used to capture the gestures and postures of the smart phone. The signals of the accelerometer and the gyroscope will be captured by an Android application and sent to a Raspberry Pi to control the robotic arm. By integrating the Internet of Things (IoT), a worldwide controllable robotic arm is achieved. The Android application is developed by using Android Studio. Python script is employed in the Raspberry Pi to develop a program that will be able to control the robotic arm and to receive the commands from the smart phone. A system with a kinematic model will be used in the Raspberry Pi to control the robotic arm. Besides, a video streaming from computer is implemented to monitor the robotic arm. The performance of the robot is investigated in term of latency of the system and IoT platform.
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Rehabilitation among stroke patients are important to provide recovery in dexterity and muscle strength, but the process involved is usually lengthy and complex. Researches have proposed many different approaches to the rehabilitation... more
Rehabilitation among stroke patients are important to provide recovery in dexterity and muscle strength, but the process involved is usually lengthy and complex. Researches have proposed many different approaches to the rehabilitation process, introducing distinct methods to exercise the patient's muscle. To assess the feasibility of the proposed procedures for rehabilitation, an accurate and consistent methodology must be applied to avoid biases while collecting the data. This paper proposes a wearable flex force smart glove to measure a patient's finger dexterity through finger flexes and presents the data in a systematic and comprehensible structure. The system allows real-time remote monitoring of data stream through the internet, and data logging for further analysis. Quantitative analysis on the system is also performed and comparisons with the commercial solutions are presented. It has been discovered that each communication between devices, from the Arduino to Raspberry Pi, and from the Raspberry Pi to Android device imposes additional time, therefore causing small but discernible performance reduction.
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Today, automobile safety has become one of the paramount focus areas by car manufacturers. The vehicles of today have increasingly grown more intelligent to keep passengers safe on the road. Apart from traffic safety, non-crash safety... more
Today, automobile safety has become one of the paramount focus areas by car manufacturers. The vehicles of today have increasingly grown more intelligent to keep passengers safe on the road. Apart from traffic safety, non-crash safety issues progressively turn out to be another prime concern. Currently, vehicular heatstroke deaths in parked vehicles are one of the major focuses in the non-crash safety domain. 2018 saw a total of 52 American children died while 90% out of 8290 calls to RSPCA concerned trapped dogs in scorching cars. Thus, we proposed a prototype system with the capability to monitor vehicle conditions and take appropriate actions to save a life. The objective of this work is to reduce the possibility of uninformed passengers, especially children, the elderly, and the pets, from unnecessary deaths or suffering from trapped car-related heatstroke. This prototype can be further enhanced to smartly communicate with other Electrical Control Units (ECUs) inside the vehicle via an in-vehicle communication network, i.e. CAN bus to further improve vehicle safety.
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Object detection, identification and classification techniques have seen many variants and improvements over past two decades. Together with Internet of Things (IoT) devices, improved computational algorithms and cloud support, real-time... more
Object detection, identification and classification techniques have seen many variants and improvements over past two decades. Together with Internet of Things (IoT) devices, improved computational algorithms and cloud support, real-time classification with low-cost devices has already been achieved. This paper discusses the real-time object detection and classification using Microsoft Custom Vision multi-class Machine Learning (ML) model operating at the Edge of IoT network. This paper further examines the use of virtual dockers or containers at the IoT edge devices for better security and isolation by decoupling physical hardware as well that supports multiple applications and services on a single hardware. The experiments are performed using emulated and simulated IoT devices on Microsoft Azure IoT platform for real-time object classification using Custom Vision Machine Learning (ML) models run directly from the edge device. The experimental results are further discussed to valid...
