Microcontroller Unit Research Articles

Microcontroller Based Sensor Interface and Its Investigation

A microcontroller (sometimes called an MCU or microcontroller unit) is an integrated circuit (IS) commonly used for a specific application designed to do certain tasks. Devices, power tools, and automobile engine control products must be controlled automatically under certain conditions, such as computers and systems. And best examples of devices, but microcontrollers are beyond these applications. Essentially, the microcontroller collects input, processes this information, and publishes a specific action based on the information collected. Microcontrollers typically operate at low speeds of 1 MHz to 200 MHz and must be designed to use less power as they are embedded in other devices with higher power consumption in other areas. The microcontroller is a particular feature inside the embedded system a small included designed to manage Round. A common microcontroller chip processor, Memory and input output (I / O) gadgets Contains. Microcontrollers embedded Controller or microcontroller unit (MCU),Vehicles, robots, every now and then the workplace Machinery, Medical Devices, Mobile Radio Transceivers, vending machines and family Found in consumables. Unnecessarily small a small aspect designed to govern functions of the portable of private computer systems. For a complex pre-very last running system (OS).

High Accuracy Software-Based Clock Synchronization Over CAN

In distributed real-time communication systems, common knowledge of the global time is crucial. It prevents message violations on the bus and allows independent components to collaborate within a real-time system on a timely basis. Systems with hard real-time requirements need to have high precision and accuracy of time. This is achieved by hardware-supported frame time-stamping mechanisms as found in dedicated protocols, such as time-triggered CAN (TTCAN), Flexray, and time-sensitive networking (TSN)-enabled Ethernet. However, many microcontroller units are not specifically designed to provide such a hardware-based solution at the communication interface. Therefore, a software-based implementation of the time synchronization algorithm is needed. Nevertheless, some commercial off-the-shelf (COTS) microcontroller units already provide an IEEE 1588-enabled Ethernet interface, including a high-precision timer module with rate correction. This module can be used for time synchronization purposes to align a set of distributed clocks via various communication interfaces. This article investigates the accuracy of software-based and hardware-supported time synchronization algorithm over the controller area network (CAN) protocol using a COTS microcontroller. As a result, we present identified jitter and delay sources as well as the achieved time accuracy. We show that using an advanced timer module combined with additional system knowledge allows submicrosecond precision and accuracies.

Heart Rate Data Transmitter through GSM

Abstract— The heart rate data collected by analogue sensors is converted to digital and sent to the concerned mobile phone through GSM module. This proposal aims to use a wireless network to continuously monitor a cardiac patient. ECG equipment are commonly used to monitor the condition of heart patients, however because of their complexity, their output cannot be communicated. As a result, a simple method known as the 'Plethysmograph' is described here to measure the pulse rate. Blood is discharged from the ventricles when the heart muscle contracts, and a pulse of pressure is delivered through the circulatory system of the human body. This pressure pulse can be felt at the tips of the fingers: blood flow can be tracked with IR sensors for this purpose. The setup is such that infrared light emitted by an IR led passes through the finger tip, and the IR energy transmitted through the finger is measured using an infrared sensor at the other end. The IR energy that is given through the blood intensity of the finger will vary slightly depending on the blood flow through the tip. These minute changes are recognised and proportionate digital pulses are created via op-amp because both sensors are positioned in a clip parallel to each other. The microcontroller unit is set up to count and display the pulses based on these signals. The LCD is used in the display part, and the same data is sent to all of the computer processor's concern cellphone number.When the system counts and displays the pulse rate per minute, if it is higher or lower than the average value, an alert is activated automatically, and data is sent to the concerned mobile phone via the GSM module. Keywords—component, formatting, style, styling, insert (key words)

Indoor Localization for Intrusion Detection and Monitoring RSSI Based

Abstract: A real time machine for Intrusion detection & monitoring primarily based on wireless sensor network technology is designed by using the use of the mote that's developed & designed in as the communication module inside the network. This dissertation tells tool-free Passive Localization with RSSI. Primary objective of this dissertation is to layout D.F.P Localization that can be redeployable, reconfigurable, smooth to apply, & operates in actual time. The embedded intrusion detection algorithm is designed so that it may cope with the limited assets, in terms of computational energy & available memory area, of the microcontroller unit (MCU) determined inside the nodes & various demanding situations & problem confronted during the real check mattress deployment & additionally proposed solutions to conquer. We come up with an opportunity algorithm primarily work on minimum Euclidean distance classifier the output suggests that localization accuracy of the method is accelerated while usage of the proposed algorithm.

A Real-Time EMG-Based Fixed-Bandwidth Frequency-Domain Embedded System for Robotic Hand.

The signals from electromyography (EMG) have been used for volitional control of robotic assistive devices with the challenges of performance improvement. Currently, the most common method of EMG signal processing for robot control is RMS (root mean square)-based algorithm, but system performance accuracy can be affected by noise or artifacts. This study hypothesized that the frequency bandwidths of noise and artifacts are beyond the main EMG signal frequency bandwidth, hence the fixed-bandwidth frequency-domain signal processing methods can filter off the noise and artifacts only by processing the main frequency bandwidth of EMG signals for robot control. The purpose of this study was to develop a cost-effective embedded system and short-time Fourier transform (STFT) method for an EMG-controlled robotic hand. Healthy volunteers were recruited in this study to identify the optimal myoelectric signal frequency bandwidth of muscle contractions. The STFT embedded system was developed using the STM32 microcontroller unit (MCU). The performance of the STFT embedded system was compared with RMS embedded system. The results showed that the optimal myoelectric signal frequency band responding to muscle contractions was between 60 and 80 Hz. The STFT embedded system was more stable than the RMS embedded system in detecting muscle contraction. Onsite calibration was required for RMS embedded system. The average accuracy of the STFT embedded system is 91.55%. This study presents a novel approach for developing a cost-effective and less complex embedded myoelectric signal processing system for robot control.

Training Up to 50 Class ML Models on 3 $ IoT Hardware via Optimizing One-vs-One Algorithm (Student Abstract)

Multi-class classifier training using traditional meta-algorithms such as the popular One-vs-One (OvO) method may not always work well under cost-sensitive setups. Also, during inference, OvO becomes computationally challenging for higher class counts K as O(K^2) is its time complexity. In this paper, we present Opt-OvO, an optimized (resource-friendly) version of the One-vs-One algorithm to enable high-performance multi-class ML classifier training and inference directly on microcontroller units (MCUs). Opt-OvO enables billions of tiny IoT devices to self learn/train (offline) after their deployment, using live data from a wide range of IoT use-cases. We demonstrate Opt-OvO by performing live ML model training on 4 popular MCU boards using datasets of varying class counts, sizes, and feature dimensions. The most exciting finding was, on the 3 $ ESP32 chip, Opt-OvO trained a multi-class ML classifier using a dataset of class count 50 and performed unit inference in super real-time of 6.2 ms.

Energy-Accuracy Aware Finger Gesture Recognition for Wearable IoT Devices.

Wearable Internet of Things (IoT) devices can be used efficiently for gesture recognition applications. The nature of these applications requires high recognition accuracy with low energy consumption, which is not easy to solve at the same time. In this paper, we design a finger gesture recognition system using a wearable IoT device. The proposed recognition system uses a light-weight multi-layer perceptron (MLP) classifier which can be implemented even on a low-end micro controller unit (MCU), with a 2-axes flex sensor. To achieve high recognition accuracy with low energy consumption, we first design a framework for the finger gesture recognition system including its components, followed by system-level performance and energy models. Then, we analyze system-level accuracy and energy optimization issues, and explore the numerous design choices to finally achieve energy–accuracy aware finger gesture recognition, targeting four commonly used low-end MCUs. Our extensive simulation and measurements using prototypes demonstrate that the proposed design achieves up to 95.5% recognition accuracy with energy consumption under 2.74 mJ per gesture on a low-end embedded wearable IoT device. We also provide the Pareto-optimal designs among a total of 159 design choices to achieve energy–accuracy aware design points under given energy or accuracy constraints.

Passenger Destination System for Commercial Vehicles

Public vehicles are predominantly the commonest and most widely used means of transport for humans in this current time. However, passengers who often commute with public vehicles mostly encounter the challenge of missing their destination primarily due to difficulties in communicating their destination to the driver, sleeping in the case of long-distance travel or the inability to recognize their destinations, and many more. In this paper, a fully functional and cost-effective passenger destination alert system for commercial vehicles (PDSCV) was developed. This designed passenger destination alert system provides solutions to the problems and as well meets the needs of some target groups such as the physically challenged. To solve these challenges, a GPS-based location module interfaced with a microcontroller unit was employed in the hardware prototype design. Destination stations were displayed and announced via an LCD and audio system respectively to generally alert all passengers on board the vehicle. The prototype also includes alert buttons beside every seat which were to be used by passengers in emergencies and to alert the driver to skip a particular terminal provided the bus is fully occupied and no passenger intends to alight. In addition to the hardware prototype, a software application was developed to provide further information to first-time travellers. The test and results from the entire system indicate a bridge in the communication gap between the driver and the passengers of commercial vehicles.

The design and realization of flexible wearable wireless music controller

<p>By using flexible sensors and micro-control units, a wireless controller that can be integrated into clothing for cross-platform music control has been designed and implemented, providing a new idea for making a simple and low-cost flexible wearable sensing system. The design and implementation of a wireless controller that can be integrated into clothing for cross-platform music control provides a new idea for the preparation of a simple and low-cost flexible wearable sensing system. Based on the flexible fabric sensing material, a simple structured sensor piece is proposed as a button for the controller with good wearing comfort. The sensor element is capable of sensing finger presses up to 15kPa. ESP32 is used as a micro-control unit for sensing signal acquisition and data processing. Using the Bluetooth chip integrated inside the ESP32, the controller can be connected with terminal devices of different platforms for wireless data transmission. The results show that the prepared wireless music controller can be stably connected with both Windows computer terminal and Android cell phone terminal, and the sensor recognition accuracy of finger press is 99.7%, which indicates that the flexible fabric sensor has a broad application prospect in the field of wearable devices.</p>

A Novel MPPT Heating Control Strategy Applied to the Induction Heating System

This study proposes an induction heating system with maximum power-point tracking (MPPT) control strategy. The system architecture adopts a 1.3 kW full-bridge series resonant circuit with a step-down transformer and adjusts the operating frequency by a microcontroller unit to improve the heating efficiency. Secondly, the proposed MPPT control strategy based on induction heating uses the relationship between the operating frequency and the system heating temperature to find the operating frequency corresponding to the maximum power point (MPP) quickly. Then, an additional hill-climbing algorithm adjusting the duty cycle is applied to reach the duty cycle corresponding to the MPP. Under the simulation and actual experimental measurement, the traditional control strategy has 76% and 68% at 500 and 750 degrees, respectively, and it takes 320 s for the system to reach 750 degrees. By contrast, the proposed MPPT control strategy achieves 96% efficiency when the system heating temperature is 500 and 750 degrees, and it only takes 120 s to reach the system heating temperature to 750 degrees. The contribution of this study is that the traditional full-bridge series resonant converter is implemented for the proposed induction heating system, where the proposed MPPT control strategy applied to the proposed induction heating system significantly has high efficiency, high stability, and high heating speed advantages, which can be accurately controlled.

DEVELOPMENT OF A BUS TRACKING AND MONITORING DEVICE USING ARDUINO NODE MICROCONTROLLER

Since the opening of Universiti Teknologi MARA Shah Alam Campus (UiTM-SAC), the university has accommodated its students by providing free bus transportation around the campus. The buses are operated based on a specific time schedule. However, students often have to wait a long time for buses because the buses do not usually arrive on schedule. In addition, the bus schedule is manually controlled by an officer, which takes time, and the data can easily be lost. Hence, the goal of this research is to develop a bus tracking and monitoring system for the UiTM-SAC. Arduino node microcontroller unit and global positioning system (GPS) sensors were used to send and receive GPS location information. The data retrieved from these sensors were displayed on an organic light-emitting diode and stored in a web-based software spreadsheet. For the experimental test, only one bus was used for collecting and analysing data. Data were immediately presented on the user interface. The results indicate that the system was able to track and monitor the bus by providing the bus’s latitude, longitude and speed. The results also revealed some key factors that affect the time required for a bus to complete a route based on users’ demands at that time. The difference in demand was 76.2%, as most students use the UiTM bus service in the morning than in the evening. In conclusion, by using the proposed bus campus tracking and monitoring system, users can easily find the exact location of buses running at the UiTM-SAC

Respiratory Activity Monitoring by a Wearable 5.8 GHz SILO With Energy Harvesting Capabilities

In this work, the design and the realization of a pocket-size sensor for breath rate detection are presented. Exploiting the self-injection locking radar technique, it is possible to perform FM-to-AM demodulation that allows the detection of the voltage peaks at the output of the sensor's receiving part. If compared with existing solutions, this device is of reduced dimensions and fully wearable; in fact, it can be worn by the user at a certain distance from the body at the chest position, and work without the need of any dedicated remotely synchronized anchor nodes nor bulky analyzers to be carried close by. As a more distinctive peculiarity, the receiving circuit is designed as an RF-to-DC rectifier in order to also enable the possibility to harvest energy that can be exploited, for instance, to feed a microcontroller unit and a transceiver with the aim of sending wirelessly the breath rate data to a laptop or a smartphone. Circuit simulations are corroborated by measurements in order to ensure the feasibility of the proposed solution.

Battery lifespan enhancement strategies for edge computing-enabled wireless Bluetooth mesh sensor network for structural health monitoring

Wireless sensor networks (WSN) offer an automated, convenient, and low-cost option for building IoT networks for monitoring the structural health of complex infrastructures. The limited bandwidth of a typical WSN is not favorable for intensive data transfer. Therefore, utilizing edge computing that allows raw data to be processed and compressed at IoT devices enables efficient data transfer to the central terminal for data storage and further analytics. However, edge computing requires an additional microcontroller unit (MCU), which significantly increases the edge device power consumption and thus reduces the device's battery lifespan. In this paper, three strategies are developed for saving the battery power of sensor devices with edge computing: (1) managing the connectivity settings of the wireless protocol settings, (2) managing the operations of the edge computing chip, and (3) adding battery capacity with parallel connections. The first strategy focuses on fine-tuning the trade-off between the WSN data throughput and power consumption. The second strategy develops two modes for power saving in certain computationally relaxing periods: Shutdown mode and Low-power mode. The Shutdown mode suspends the operations of the edge computing chip, allowing the edge computing chip to run for a limited time per day. The Low-power mode allows continuous operation of the edge computing chop at low clock speed, which consumes less current. The third strategy doubles the device lifespan by doubling the battery charge capacity using parallel connections. Combining all three strategies significantly enhances the sensor battery lifespan from three weeks to at least six months, notably reducing the frequency of on-site hardware maintenance while providing smooth data transfer due to edge computing.

A Smart GSM-Based Home Electrical Appliances Remote Control System

Energy control systems have over the years experienced significant transformation due to technological innovations. Its importance has led to the development of a few models aimed at realizing home automation and resolving energy wastage. Wise use of electricity helps a nation to become more energy-efficient, reduces the environmental impact, saves money on the electricity bills, and keeps the nation’s electricity supply more reliable. This paper presents a prototype design to reduce the electricity wastage in Ghanaian homes and probably offices. A Global System for Mobiles (GSM) module is used for receiving short message service (SMS) from user’s mobile phone that automatically enable the controller to take any further action such as to switch ON or OFF the home electrical appliances like light, air-conditioner, fan etc. The system is activated when user sends the SMS to the microcontroller and upon receiving the SMS command, the microcontroller unit then automatically controls the home electrical appliances by switching ON or OFF the device accordingly. A system prototype was developed and tested successfully. The system provides an effective mechanism to aid the efficient utilization of power in a developing country such as Ghana

Remote Fault Monitoring of Substation Primary Equipment Using Embedded Technology

We know that due to huge demand of electricity the size and complexity of distribution network has grown & because of that automation of substation becomes very important to increase its efficiency as well as to improve the quality of power being delivered at users end. So, our prototype will monitor the real time parameters like voltage, temperature, current, power of substation with Micro-controller unit & if any faults occur in distribution transformer it will gives indication during fault condition and immediately relay operates. The data of measured parameters will be available on smartphone/ desktop. This allows us to save time and money at the substation by reducing labour cost. Also, the functioning effectiveness, efficiency and power quality will undoubtedly improve with this approach.

An Ultra-Low-Power Strain Sensing Node for Long-Range Wireless Networks in Carbon Nanotube-Based Materials

The application of flexible electronics to device-engineering technologies has enabled the manufacture of low-cost, lightweight, extensible, and foldable sensors. However, despite the efficient response of composite materials for the detection of signal stimuli reported in the state-of-art literature, there is an area of opportunity for the implementation of ultra-low-power wireless sensor networks (WSN) with novel flexible materials in precision medicine, structural health monitoring, environmental sensing, wearables and applications based on the Internet of Things (IoT). This article proposes a portable strain sensing node based on multiwall carbon nanotubes (MWCNTs)/polypropylene(PP) composites for Long-Range (LoRa) wireless networks with IoT connectivity. The nanostructured sensor node with 4 wt% MWCNTs shows high piezoresistive sensitivity with gage factors of ~ 4.5. A system identification problem is conducted following a constrained optimization model, which estimates the sensor errors due to nonlinearity and system parameters, providing a stable strain response with high accuracy. An energy management strategy is also implemented for the efficient integration of a microcontroller unit in combination with a wireless LoRa communication transceiver, enabling the utilization of flexible composite materials into a wireless nanostructured sensing network with ultra-low-power consumption of 0.8705 mW. The experimental results of the MWCNT/PP strain sensing node show the feasibility for a variety of IoT-WSN applications.

Integrated Sensing and Computing for Wearable Human Activity Recognition with MEMS IMU and BLE Network

Abstract The miniature sensor devices and power-efficient Body Area Networks (BANs) for Human Activity Recognition (HAR) have gained increasing interest in different fields, including Daily Life Assistants (DLAs), medical treatment, sports analysis, etc. The HAR systems normally collect data with wearable sensors and implement the computational tasks with a host machine, where real-time transmission and processing of sensor data raise a challenge for both the network and the host machine. This investigation focuses on the hardware/software co-design for optimized sensing and computing of wearable HAR sensor networks. The contributions include (1) design of a miniature wearable sensor node integrating a Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS IMU) with a Bluetooth Low Energy (BLE) in-built Micro-Control Unit (MCU) for unobtrusive wearable sensing; (2) task-centric optimization of the computation by shifting data pre-processing and feature extraction to sensor nodes for in-situ computing, which reduces data transmission and relieves the load of the host machine; (3) optimization and evaluation of classification algorithms Particle Swarm Optimization-based Support Vector Machine (PSO-SVM) and Cross Validation-based K-Nearest Neighbors (CV-KNN) for HAR with the presented techniques. Finally, experimental studies were conducted with two sensor nodes worn on the wrist and elbow to verify the effectiveness of the recognition of 10 virtual handwriting activities, where 10 recruited participants each repeated an activity 5 times. The results demonstrate that the proposed system can implement HAR tasks effectively with an accuracy of 99.20 %.

A High Gain Modified Quadratic Boost DC-DC Converter with Voltage Stress Half of Output Voltage

The application of the high gain boost DC-DC converter is gaining more attention due to an increasingly wide range of applications for sustainable green energy solutions, as well as other high voltage applications. In this study, a modified high gain quadratic boost converter is proposed using a single switch. The proposed topology is a member of the family of the non-isolated category with a common ground feature and can operate in a wide range of duty ratios, and is able to provide the required voltage gain. In this proposed circuit configuration, a dual voltage boost cell was formed by incorporating two capacitors in series with two inductors of a conventional quadratic boost converter. Additionally, a capacitor was integrated with a second voltage boost cell. This special configuration increases the voltage gain as well as reduces the voltage stress across the switch. To show its feasibility, a 200-W prototype setup with 48 V input and 400 V output was designed, and the required PWM signal was fed from the microcontroller unit. A detailed analysis of the design parameters and losses are formulated and are shown in this paper. The simulation was performed in SIMPLIS software, and the experimental results agreed with the obtained output voltage gain. The proposed topology showed a peak efficiency of 94.5% at 150-W output power after considering the power losses in all the components of the PCB.

Real Time Power Control in a High Voltage Power Supply for Dielectric Barrier Discharge Reactors: Implementation Strategy and Load Thermal Analysis

Atmospheric-pressure plasma treatments for industrial and biomedical applications are often performed using Dielectric Barrier Discharge reactors. Dedicated power supplies are needed to provide the high voltage frequency waveforms to operate these nonlinear and time-dependent loads. Moreover, there is a growing technical need for reliable and reproducible treatments, which require the discharge parameters to be actively controlled. In this work, we illustrate a low-cost power supply topology based on a push–pull converter. We perform experimental measurements on two different reactor topologies (surface and volumetric), showing that open loop operation of the power supply leads to a temperature and average power increase over time. The temperature increases by ΔTvol~120 °C and ΔTsup~70 °C, while the power increases by ΔPvol~78% and ΔPsup~60% for the volumetric (40 s) and superficial reactors (120 s), respectively. We discuss how these changes are often unwanted in practical applications. A simplified circuital model of the power supply–reactor system is used to infer the physical relation between the observed reactor thermal behavior and its electrical characteristics. We then show a control strategy for the power supply voltage to ensure constant average power operation of the device based on real-time power measurements on the high voltage side of the power supply and an empirical expression relating the delivered power to the power supply output voltage. These are performed with an Arduino Due microcontroller unit, also used to control the power supply. In a controlled operation the measured power stays within 5% of the reference value for both configurations, reducing the temperature increments to ΔTvol~80 °C and ΔTsup~44 °C, respectively. The obtained results show that the proposed novel control strategy is capable of following the transient temperature behavior, achieving a constant average power operation and subsequently limiting the reactor thermal stress.

Real Time Monitoring Based Smart Farming

Agriculture has long played a key role in countries like India, and agricultural challenges are becoming increasingly widespread these days Internet of Things (IoT) is a network of devices that are self-configured. Intelligent Smart Farming IoT-based gadgets are slowly but steadily creating enhancement in agro production, and improving it but also by lowering costs and reducing waste. Real-time Monitoring based Smart farming has the potential to be a pillar in the country's development. The Internet of Things (IoT) revolutionized every aspect of the Common man's life by making everything intelligent, fast and smart. By doing everything smarter and smarter, Internet of Things (IoT) transformed everything for common man's existence. The objective of our project is to demonstrate IoT-based Smart Farming System to assist farmers in obtaining real-time moisture and temperature data, as well as soil moisture (Sparkfun soil moisture sensors) efficiency ecological surveillance, allowing them to improve overall yield and harvest quality. The Internet of Things-based Realtime Monitoring Based Smart Farming System combines Arduino Technology (Node MCU) with a wifi Microcontroller unit to generate a Real time data feed that can be viewed via Thingsspeak.com.