IoT Sensor System Research Articles

Utility Maximization for Multi-UAV-Assisted IoT Sensor Systems With NOMA

Utility Maximization for Multi-UAV-Assisted IoT Sensor Systems With NOMA

Wireless IoT universal approach based on Allan variance method for detection of artificial vibration signatures of a DC motor's shaft and reconstruction of the reference signal

In this paper, a workbench for remote control of DC motors is proposed. We intend to monitor and control rotating machines. Artificial failures are simulated by injecting different signals into the rotating motor's shaft. A comprehensive, original, and novel approach combining mathematical models, physical phenomena, and smart measurement methods is proposed to eliminate fluctuation faults caused by IoT sensor systems. These consist of a whole set of sensors (Accelerometer in Micro Electro Mechanical Systems [MEMS] technology, etc.) linked to a wireless node which constitutes a monitoring and control generic system of a DC motor running locally or via a remote control through an Internet platform. A reliability test of the IoT sensor system and an exploration of a proposed experimental bench in two measurement environments are successfully achieved. The results prove the reliability of devices for possible detection of acceleration signals corresponding to different speeds and injected vibrations with different forms and frequencies. A universal new approach, based on the Allan VARiance method, that has been proven robust when various disturbing signals are combined, has been successfully implemented to identify artificial vibration signatures. A reconstruction of MEMS sensor outputs using genetic algorithms is successfully fulfilled to get a compromise between the time of data acquisition and the time of processing via a learning phase of our system by means of a pseudo calibration of each motor applying our pseudo real-time control system. After the calibration phase, our control system aims to space out the measurements without degrading the effectiveness of the monitoring process.

Smart Classroom for Electricity-Saving with Integrated IoT System

Electricity-saving can be achieved through the efficient use of energy such as turning off lights and electrical appliances when not in use. Therefore this work proposed the smart classroom for electricity-saving with an integrated IoT System to prevent wasting electricity in the classroom. Smart Classroom means that it will detect and count the number of students entering and exiting the classroom by using a sensor system automatically. The main objective of this work is to control the lighting systems and fans by using the IoT application and sensor system. This means that when the sensor is triggered the sensor will send data to the Blynk application software using IoT to display the status of the classroom. This proposed work is also able to detect whether a classroom is available to use or not based on the presence of people. If the classroom is being used the Blynk application software will show the lamp and fan are ON. Otherwise the lamps and fans are OFF if there are no people in the classroom. The result successfully shows that if the first student entering the classroom all the lamps and fans are ON. While if the last student exiting the classroom all the lamps and fans are OFF. This result also indicates that electricity can be saved if all appliances in the classroom are switch OFF at the right time.

Towards an Occupancy-Oriented Digital Twin for Facility Management: Test Campaign and Sensors Assessment

This study focuses on calibration and test campaigns of an IoT camera-based sensor system to monitor occupancy, as part of an ongoing research project aiming at defining a Building Management System (BMS) for facility management based on an occupancy-oriented Digital Twin (DT). The research project aims to facilitate the optimization of building operational stage through advanced monitoring techniques and data analytics. The quality of collected data, which are the input for analyses and simulations on the DT virtual entity, is critical to ensure the quality of the results. Therefore, calibration and test campaigns are essential to ensure data quality and efficiency of the IoT sensor system. The paper describes the general methodology for the BMS definition, and method and results of first stages of the research. The preliminary analyses included Indicative Post-Occupancy Evaluations (POEs) supported by Building Information Modelling (BIM) to optimize sensor system planning. Test campaign are then performed to evaluate collected data quality and system efficiency. The method was applied on a Department of Politecnico di Milano. The period of the year in which tests are performed was critical for lighting conditions. In addition, spaces’ geometric features and user behavior caused major issues and faults in the system.Incorrect boundary definition: areas that are not covered by boundaries; thus, they are not monitored

(Invited) Development of CMOS-MEMS Cointegrated Pressure Sensor Using Minimal Fab Process

The Minimal Fab concept was proposed in 2008 to produce low-volume customized devices with a low investment cost [1]. The different points of Minimal Fab compared with those of the conventional Mega Fab are as follows. (a) Wafer size is half-inch (12.5 mm), (b) the transferring and processing of the wafer are performed with a cleanliness level identical to that of a super clean room, and (c) the machine used compact dimensions of 144 cm height, 30 cm width, and 45 cm depth. Since the proposal of the Minimal Fab concept, many Minimal Fab machines and Minimal Fab processes have been developed actively for the fabrication of CMOS integrated circuits [2, 3]. However, the Minimal Fab process for MEMS sensor fabrications has not been developed sufficiently. In this work, we develop the CMOS-MEMS cointegrated process using the Minimal Fab deep-RIE and mask aligner. By using the developed process, we also fabricate and characterize the digital type CMOS-MEMS pressure sensor. The pressure sensing element in the CMOS-MEMS pressure sensor is the CMOS ring oscillator with the longitudinal PMOSFETs located at the edge areas of a thin circular diaphragm. In the device fabrication, we used (100) oriented half-inch SOI wafers, and the source-drain (SD) regions of the MOSFETs were patterned along with the <110> direction to effectively utilize mechanical stress induced drain current variations. As the gate material, we used a 30-nm-thick PVD-TiN layer to obtain a suitable logic gate threshold voltage of the CMOS invertors. The circular diaphragm was fabricated using Minimal Fab mask aligner and deep-RIE. It was confirmed that the oscillation frequency changes from 360 to 400 kHz by changing pressures from -40 to +40 kPa in the fabricated CMOS-MEMS cointegrated pressure sensor chip. The developed CMOS-MEMS pressure sensor is suitable for the application to the battery drive IoT sensor systems owing to its low power consumption. [1] S. Hara et al., J. Jpn. Precis. Eng., vol. 77, no. 3, p. 249, 2011. [2] Y. X. Liu et al., Jpn. J. Appl. Phys. 56, p. 06GG01-1. [3] Y. X. Liu et al., J. Appl. Phys. 57, p. 06HD03-1.

(Invited) Development of CMOS-MEMS Cointegrated Pressure Sensor Using Minimal Fab Process

PVD-TiN metal gate PMOSFETs and CMOS ring oscillators have successfully been fabricated on circular diaphragms using the developed Minimal Fab CMOS-MEMS cointegrated gate-last process, and their electrical characteristics have systematically been investigated by changing applied pressures to the diaphragms. It was found that the drain current variation (dId) in the <110> channel PMOSFETs is larger than that in the <100> channel ones. The origin of dId is the mechanical stress-induced mobility change. It was also confirmed that the oscillation frequency of the fabricated CMOS ring oscillator on a circular diaphragm changes from 372 to 405 kHz at different pressures of -30 and +30 kPa. This result implies that the fabricated CMOS-MEMS cointegrated sensor chip is operated as a pressure sensor. The developed CMOS-MEMS cointegrated pressure sensor is suitable for the application to the battery drive IoT sensor systems because the all CMOS integration of the sensor has a low-power consumption.

Propeller-based Underwater Piezoelectric Energy Harvesting System for an Autonomous IoT Sensor System

While there is a demand for energy harvesting in environments with water, such as rivers, lakes seas, it has been difficult to use energy harvesting, especially piezoelectricity, because of the waterproof problem and the low output scale. Here, we report a propeller-based underwater piezoelectric energy harvester consisting of a propeller, hitting sticks and a piezoelectric module. The hitting sticks spin with a rotating axis connected to a propeller rotated by water flow and hit a piezoelectric cantilever beam. Unlike previous tip mass method, a newly applied technique makes it possible to match a frequency by easily controlling the bending length of a piezoelectric module using an acrylic plate to find the maximum output power. For reliability, we performed an experiment at 1.2 m/s, which is the actual water flow rate of the Han River in South Korea, and a frequency of 24.5 Hz occurred with four hitting sticks. The frequency-matched bending length was 80 mm (acrylic plate length: 10 mm). Then, impedance matching was carried out: At a resistance of 10.8 kΩ, an output power of 17 mWrms and a power density of 57.4 mW/cm3 were obtained. This result is one of the highest results in a field of similar piezoelectric energy harvesting devices considering challenging conditions that occur in real environments. Finally, the system was applied to an LED light system, one of applications under water, and succeeded in operating a total of 972 LEDs with only one piezoelectric device. This research proves the potential and the feasibility of applying a piezoelectric energy harvesting system to a real underwater environment.

Significant power enhancement method of magneto-piezoelectric energy harvester through directional optimization of magnetization for autonomous IIoT platform

Unlike previous piezoelectric energy harvesters that generate electrical energy from a magnetic field according to the magnetic strength or magnetostrictive material, the proposed method achieves significant power enhancement using directional optimization of magnetization. This method can serve as a ubiquitous autonomous energy source that converts a magnetic field into usable electrical energy in a wireless sensor network for an (Industrial) Internet of Things (IIoT). The key approach in the proposed model is to increase of the Lorentz force by vertically adjusting the magnetic flux direction of a power cable and the magnetic direction of a tip magnet. In the simulation, a 3592 times higher y-axis Lorentz force was obtained in the vertical pole array, which resulted in about a 1.6 times higher output voltage. Then, we experimentally compared the electrical output performance of six different types of pole array according to the size and direction of the tip magnet. In a one-tip magnet (10 × 10 × 10 mm3), the output power values were 2.34 mW (Vertical) and 1.23 mW (Horizontal) at 8 kΩ matching impedance. For two-tip magnets (20 × 10 × 10 mm3), the output power values of the harvester were 39.2 mW (Planar-Vertical), 18.4 mW (Orthogonal-Vertical), 8.64 mW (Planar-Horizontal), and 0.05 mW (Orthogonal-Horizontal) at 5 kΩ matching impedance. It was found that the power generation differed by 2.13 to 784 times. With this method of power enhancement using multi-disciplinary research, we successfully constructed autonomous IoT and IIoT sensor systems for smart homes, smart buildings and smart factories.

Deep CNN for Indoor Localization in IoT-Sensor Systems.

Currently, indoor localization is among the most challenging issues related to the Internet of Things (IoT). Most of the state-of-the-art indoor localization solutions require a high computational complexity to achieve a satisfying localization accuracy and do not meet the memory limitations of IoT devices. In this paper, we develop a localization framework that shifts the online prediction complexity to an offline preprocessing step, based on Convolutional Neural Networks (CNN). Motivated by the outstanding performance of such networks in the image classification field, the indoor localization problem is formulated as 3D radio image-based region recognition. It aims to localize a sensor node accurately by determining its location region. 3D radio images are constructed based on Received Signal Strength Indicator (RSSI) fingerprints. The simulation results justify the choice of the different parameters, optimization algorithms, and model architectures used. Considering the trade-off between localization accuracy and computational complexity, our proposed method outperforms other popular approaches.

A wearable IoT aldehyde sensor for pediatric asthma research and management

Mechanistic studies and personalized managements of pediatric asthma require objective measures of environmental exposure metrics correlated with patient’s physiological responses. Here we report a cloud-based wearable IoT sensor system which can measure an asthma patient’s exposure to aldehydes, a known class of airway irritants, in real-life settings. The wrist-watch shaped sensor can measure formaldehyde levels in air from 30ppb to 10ppm using fuel cell technology, and continuously operate over 7 days without recharging. The sensor wirelessly uploads data to an Android smartphone via Bluetooth Low Energy (BLE). The smartphone also functions as a gateway to a cloud-based informatics system which handles sensor data storage, management and analytics. Potential applications of this IoT sensor system include epidemiological studies of asthma development and exacerbations, personalized asthma management and environmental monitoring.

Design of Wideband Voltage Controlled Oscillator with Capacitor-Bank for IoT Sensor System

본 논문에서는 IoT 센서 시스템에 적용 가능한 광대역 전압 제어 발진기의 설계 및 구현에 대하여 기술하였다. 본 논문에 제안된 센서 시스템은 지역 및 국가별로 상이한 주파수를 사용하여, 센서 시스템내 각 모듈에 대해 광대역 특성이 요구된다. 따라서 제안한 전압 제어 발진기는 13단 캡-뱅크를 적용하여 광대역 특성을 구현하였으며, NP 코어 구조를 이용하여 고속 저잡음 특성을 갖도록 설계하였다. 제안한 전압 제어 발진기 구조는 0.18㎛ CMOS 기술을 사용하여 제작하였으며, 0.89*0.42㎟의 크기를 가진다. 전압 제어 발진기를 칩으로 제작하여 측정한 결과 출력 주파수 범위는 1485.8∼2020MHz이며, 위상 잡음은 100KHz 오프셋에서 -93.15dBc/Hz의 특성을 나타내었다.