Low-priced Sensor Research Articles

A review of IoT security and privacy using the Blockchain to Boost Data Integrity and Privacy

The Internet of Things (IoT) is an emerging technology. It enables users to exchange their data and resources by linking devices across the IoT network, resulting in a more relaxed and connected lifestyle. It allows real-time data to be delivered to end-user applications and systems via sensing, actuation, communication, computing, networking, and storage. It can transfer data across a network without requiring human intervention or computer-to-computer interaction. It makes it possible to detect the various sensors around the world through low-priced sensor devices. IoT Networking defines communication or inter-connection between Peer-to-Peer (P2P) either through a connected medium (Wired) or unconnected medium (Wireless) to procure a secure transmission of data. Blockchain is a peer-to-peer network where peers can communicate and do transactions without the need for centralized authority. It allows data to be stored and transferred in a safe and interconnected method. This section includes a literature review on the centralized IOT system model, highlighting the limitations of the centralized IoT system and blockchain security in IoT. This research study's systematic evaluation is processed based on the reviews of the literature available with recent advancements and inventions through patents, articles, conference papers, and journals. Also, the related work with IoT systems for data privacy and security issues and applying Blockchain technology to IOT are discussed.

A review of IoT security and privacy using the Blockchain to Boost Data Integrity and Privacy

The Internet of Things (IoT) is an emerging technology. It enables users to exchange their data and resources by linking devices across the IoT network, resulting in a more relaxed and connected lifestyle. It allows real-time data to be delivered to end-user applications and systems via sensing, actuation, communication, computing, networking, and storage. It can transfer data across a network without requiring human intervention or computer-to-computer interaction. It makes it possible to detect the various sensors around the world through low-priced sensor devices. IoT Networking defines communication or inter-connection between Peer-to-Peer (P2P) either through a connected medium (Wired) or unconnected medium (Wireless) to procure a secure transmission of data. Blockchain is a peer-to-peer network where peers can communicate and do transactions without the need for centralized authority. It allows data to be stored and transferred in a safe and interconnected method. This section includes a literature review on the centralized IOT system model, highlighting the limitations of the centralized IoT system and blockchain security in IoT. This research study's systematic evaluation is processed based on the reviews of the literature available with recent advancements and inventions through patents, articles, conference papers, and journals. Also, the related work with IoT systems for data privacy and security issues and applying Blockchain technology to IOT are discussed.

Determining accurate hand positions in three-dimensional space using twin-axis electrogoniometer sensors

Electrogoniometers are low price sensors which are easily attached to the body in any environment. Although electrogoniometer sensors are typically used for angular measurements, they can also be used to determine position. This study aimed to accurately determine hand position during the performance of five daily life activities using two electrogoniometer sensors to measure shoulder and elbow angles simultaneously. The measurement of joint angles involves some errors which are divided into intrinsic and extrinsic errors. These errors cause considerable inaccuracies in the estimated hand positions. To overcome this issue, the errors identified are compensated for in two phases, the angular phase and the positional phase, in which a polynomial function and an Elman neural network are used for error compensation, respectively. The derived hand trajectories and the decrease of theroot mean square error at every stage of the error compensation, along with the variance accounted for of the Elman networks for each task, show the effectiveness of the proposed method.

Fully Printed Disposable IoT Soil Moisture Sensors for Precision Agriculture

Digitization of industrial processes using new technologies (IoT—Internet of Things, IoE—Internet of Everything), including the agriculture industry, are globally gaining growing interest. The precise management of production inputs is essential for many agricultural companies because limited or expensive sources of water and nutrients could make sustainable production difficult. For these reasons, precise data from fields, plants, and greenhouses have become more important for decision making and for the proper dosage of water and nutrients. On the market are a variety of sensors for monitoring environmental parameters within a precise agricultural area. However, the high price, data storage/transfer functionality are limiting so cost-effective products capable to transfer data directly to farmers via wireless IoT networks are required. Within a given scope, low-price sensor elements with an appropriate level of sensor response are required. In the presented paper, we have developed fully printed sensor elements and a dedicated measuring/communicating unit for IoT monitoring of soil moisture. Various fabrication printing techniques and a variety of materials were used. From the performed study, it is obvious that fully printed sensor elements based on cheap and environmentally friendly carbon layers printed on the wood substrate can compete with conventionally made sensors based on copper.

Photoelectric Sensor for Fast and Low-Priced Determination of Bi- and Triphasic Segmented Slug Flow Parameters.

Applying multiphase systems in microreactors leads to an intensification of heat and mass transport. Critical aspects of the well-studied segmented slug-flow, such as bubble generation and pump control, can be automated, provided a robust sensor for the reliable determination of velocity, phase lengths, and phase ratio(s) is available. In this work, a fast and low-priced sensor is presented, based on two optical transmission sensors detecting flow characteristics noninvasively together with a microcontroller. The resulting signal is mainly due to refraction of the bubble-specific geometries as shown by a simulation of light paths. The high performance of the processing procedure, utilizing the derivative of the signal, is demonstrated for a bi- and triphasic slug flow. The error of <5% is entirely reasonable for the purpose envisaged. The sensor presented is very fast, robust, and inexpensive, thus enhancing the attractiveness of parallelized capillary reactors for industrial applications.

Optimal sensor fusion and position control of a low-price self-driving vehicle in short-term operation conditions

Real-time estimation of the absolute position and orientation plays a critical role in the control and path planning of a self-driving vehicle. Global positioning systems (GPSs) are used to estimate the absolute position of a vehicle from satellite signals, but their reliability and accuracy are not sufficient for precise control. An inertial navigation system (INS) is often used to complement the GPS, but it is always subjected to a drift problem due to integration. Such a problem has been solved by utilizing a high performance GPS, an INS, a vision sensor, a radar, a laser scanner, or their combination. However, these sensor systems are very expensive compared to the price of common commercial vehicles, which hinders the popularization of self-driving vehicles. Moreover, the target users of self-driving vehicles are most likely the elderly, as well as the blind, and thus the price is an important factor in the system design. In this paper, a sensor fusion method for a low-price self-driving vehicle and real-time path planning algorithm without a laser scanner are introduced. The proposed low-price sensor system consists of a GPS, an inertial measurement unit (IMU) with a three-axes accelerometer, a three-axes gyroscope, and a three-axes magnetometer, an encoder at the real wheels, and a potentiometer that measures the steering angle. The overall price is less than 300 USD. For the complete estimation of the absolute position and orientation of the vehicle, the proposed method estimates the driving velocity using a kinematic Kalman filter, then the orientation angle and absolute position are calculated by the recursive least squares method. The obtained information is then used for the real-time control of a self-driving vehicle. The proposed method is verified through simulation studies and by experimental results.

A Flat Polymeric Membrane Sensor for Carbon Dioxide/Nitrogen Gas Mixture

A gas sensor was developed to measure the concentration of binary gas mixtures. This sensor works based on the permeability change of different gas mixtures across the polymeric membranes. Although high values of permeability and selectivity are needed for an ideal separation, the performance of this sensor mainly depends on the permeability factor. Polysulfone and silicone rubber were applied as the membrane base and coat, respectively. Moreover, in contrast to existing polymeric sensors that use hollow fibers, the present sensor is made of flat membranes. This new design is cheaper, smaller, and easier to use in comparison to the hollow fiber polymeric sensors. In order to test the sensor applicability, nitrogen and carbon dioxide were used as model gases. The effect of pressure on the response time and sensor accuracy was studied for the aforementioned gases. The response time (T95%) of this low price sensor was 50 s, and the tolerance of measuring concentration was approximately 1.4% at 2 bar feed pressure. Also, increasing the feed pressure can improve the response time or accuracy of the sensor.

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

Geomagnetic field-based localization with bicubic interpolation for mobile robots

This paper proposes a novel geomagnetic field-based SLAM (simultaneous localization and mapping) technique for application to mobile robots. SLAM is an essential technique for mobile robots such as robotic vacuum cleaners to perform their missions autonomously. For practical application to commercialized robotic vacuum cleaners, the SLAM techniques should be implemented with low-priced sensors and low-computational complexity. Most building structures produce distortions in the geomagnetic field and variation of the field over time occurs with extremely low frequency. The geomagnetic field is hence applicable to mobile robot localization. The proposed geomagnetic field SLAM uses only the geomagnetic field signals and odometry data to estimate the robot state and the geomagnetic field signal distribution with low computational cost. To estimate the signal strength of the geomagnetic field, bicubic interpolation, an extension of cubic interpolation for interpolating surfaces on a regular grid, is used. The proposed approach yields excellent results in simulations and experiments in various indoor environments.

MIR-ATR sensor for process monitoring

A mid-infrared attenuated total reflectance (MIR-ATR) sensor has been developed for chemical reaction monitoring. The optical setup of the compact and low-priced sensor consists of an IR emitter as light source, a zinc selenide (ZnSe) ATR prism as boundary to the process, and four thermopile detectors, each equipped with an optical bandpass filter. The practical applicability was tested during esterification of ethanol and formic acid to ethyl formate and water as a model reaction with subsequent distillation. For reference analysis, a Fourier transform mid-infrared (FT-MIR) spectrometer with diamond ATR module was applied. On-line measurements using the MIR-ATR sensor and the FT-MIR spectrometer were performed in a bypass loop. The sensor was calibrated by multiple linear regression in order to link the measured absorbance in the four optical channels to the analyte concentrations. The analytical potential of the MIR-ATR sensor was demonstrated by simultaneous real-time monitoring of all four chemical substances involved in the esterification and distillation process. The temporal courses of the sensor signals are in accordance with the concentration values achieved by the commercial FT-MIR spectrometer. The standard error of prediction for ethanol, formic acid, ethyl formate, and water were 0.38 mol L − 1, 0.48 mol L − 1, 0.38 mol L − 1, and 1.12 mol L − 1, respectively. A procedure based on MIR spectra is presented to simulate the response characteristics of the sensor if the transmission ranges of the filters are varied. Using this tool analyte specific bandpass filters for a particular chemical reaction can be identified. By exchanging the optical filters, the sensor can be adapted to a wide range of processes in the chemical, pharmaceutical, and beverage industries.

Fuzzy Inference System: Short Review and Design

Fuzzy control provides a formal methodology for representing, manipulating, and implementing a human’s heuristic knowledge about how to control a system. The fuzzy control can be applied in cases where the control processes are too complex to analyze by conventional quantitative techniques or the available sources of information are interpreted qualitatively, inexactly, or uncertainly. Fuzzy controller offers many advantages to compare with other approaches to deal with uncertainty. Furthermore, fuzzy logic is well suited for low-cost implementations based on low-priced sensors, small resolution convertors of analog to digital and 4-8bit microcontroller. Such systems can be effortlessly improved by adding new rules to enhance performance or add new features. In several cases, fuzzy control can be used to advance existing conventional control systems by appending an additional layer of intelligence to the existing control method. In this research, an extensive insight of Fuzzy Inference System steps design are presented, as well as, the emphases on the fusion of fuzzy control concepts with nowadays wireless sensor networks. Review of fuzzy superior features contrary to traditional and intelligent controlling paradigms is obviously stated. Finally, the adoption of Fuzzy Inference System (FIS) approach to control problems with wireless sensor actor network is due to a number of reasons. Its algorithm needs a small size of memory, less time of execution; indeed it necessitates less mathematics than other controlling approaches.

경량 모바일매핑시스템을 위한 도심지 내 MEMS 기반 IMU/GPS 통합센서(MTi-G) 특성 연구

MEMS(Micro Electro Mechanical System)기술이 발전하여 작고 저렴한 IMU(Initial Measurement Unit)와 GPS(Global Positioning System)통합센서가 생산되어 다양한 분야에서 활용되고 있다. 본 연구에서는 모바일매핑시스템을 경량화하기 위해서 MEMS 기반 IMU/GPS 통합센서가 적합할 것으로 판단하고 XSens사 MEMS 기반 IMU/GPS 통합센서(MTi-G)의 특성 분석을 위한 실험을 수행하였다. 차량 대시보드에 통합센서를 고정하고 인천 송도 국제도시 도로구간과 터널구간을 주행하여 후처리 과정을 거치지 않은 좌표성과를 취득하였다. 전반적으로 위치결정 성과가 양호했지만 일부 구간(정지구간, 과속방지턱, 터널구간 등)에서 센서 특성, XKF(칼만필터) 특성 및 GPS 신호 수신환경 제한으로 인해 양호하지 못한 부분이 확인되었다. 실험결과 경량 모바일매핑시스템의 활용 가능성을 확인할 수 있었으며, 향후 다양한 GPS 신호 수신환경과 주행 조건에서의 실험과 보다 정밀한 정확도 분석이 요구된다. With the development of MEMS, small and low-priced sensors integrating IMU and GPS have produced and exploited for diverse field. In this research, we have judged that MEMS-based IMU/GPS sensor is suitable for light-weighted mobile mapping system and carried out experiments to analyze the characteristics of MTi-G, which was developed from XSens company. From a sensor which fixed to dashboard, coordinates results with no post-processing were achieved for test area. On the whole, the results show satisfactory performances but some errors also were discovered from parts of the road due to sensor properties, XKF characteristics and GPS reception environment. We could confirm the potential of light-weighted mobile mapping system. Experiments considering various GPS reception environments and road condition and more detailed level of accuracy analysis will be performed for further research.

A Data Fusion System for Attitude Estimation of Low-cost Miniature UAVs

Miniature unmanned aerial vehicles (UAVs) have attracted wide interest from researchers and developers because of their broad applications. In order to make a miniature UAV platform popular for civilian applications, one critical concern is the overall cost. However, lower cost generally means lower navigational accuracy and insufficient flight control performance, mainly due to the low graded avionics on the UAV. This paper introduces a data fusion system based on several low-priced sensors to improve the attitude estimation of a low-cost miniature fixed-wing UAV platform. The characteristics of each sensor and the calculation of attitude angles are carefully studied. The algorithms and implementation of the fusion system are described and explained in details. Ground test results with three sensor fusions are compared and analyzed, and flight test comparison results with two sensor fusions are also presented.

Concurrent localization of multiple robots

A concurrent localization method for multiple robots using ultrasonic beacons is proposed. This method provides a high-accuracy solution using only low-price sensors. To measure the distance of a mobile robot from a beacon at a known position, the mobile robot alerts one beacon to send out an ultrasonic signal to measure the traveling time from the beacon to the mobile robot. When multiple robots requiring localization are moving in the same block, it is necessary to have a schedule to choose the measuring sequence in order to overcome constant ultrasonic signal interference among robots. However, the increased time delay needed to estimate the positions of multiple robots degrades the localization accuracy. To solve this problem, we propose an efficient localization algorithm for multiple robots, where the robots are in groups of one master robot and several slave robots. In this method, when a master robot calls a beacon, all the group robots simultaneously receive an identical ultrasonic signal to estimate their positions. The effectiveness of the proposed algorithm has been verified through experiments.

A Study for Sensor Selection LQ Problem

Although it is recognized that linear control theory has been established mostly, but depending on realistic conditions there remain unsolved control problems. As an example we will discuss the sensor selection LQ problem in this paper. Recent sensor technology makes a process to arrange many low-priced sensors possible. In such case we can expect more effective real-time control by changing sensors properly. This problem will be an essential control problem, but it has not been discussed in the literature. This is because of the combinatorial property of the problem solution. In this paper, we first propose the concept of “the comparability of sensors” and yield a result for the uniqueness of optimal solution. Next, we extend the problem in the case of use of observer and yield a sufficient condition for existence of the unique solution.