Wireless Gateway Research Articles

Joint Optimization on Trajectory, Data Relay, and Wireless Power Transfer in UAV-Based Environmental Monitoring System

In environmental monitoring systems based on the Internet of Things (IoT), sensor nodes (SNs) typically send data to the server via a wireless gateway (GW) at regular intervals. However, when SNs are located far from the GW, substantial energy is expended in transmitting data. This paper introduces a novel unmanned aerial vehicle (UAV)-based environmental monitoring system. In the proposed system, the UAV conducts patrols in the designated area, and SNs periodically transmit the collected data to the GW or the UAV. This transmission decision is made while taking into account the respective distance between both the GW and the UAV. To ensure a high-quality environmental map, characterized by a consistent collection of a satisfactory amount of up-to-date data while preventing energy depletion in the SNs and the UAV, the UAV periodically decides on three types of UAV operations. These decisions involve deciding where to move, deciding whether to relay or aggregate the data from the SNs, and deciding whether to transfer energy to the SNs. For the optimal decisions, we introduce an algorithm, called DeepUAV, using deep reinforcement learning (DRL) to make decisions in UAV operations. In DeepUAV, the controller continually learns online and enhances the UAV’s decisions through trial and error. The evaluation results indicate that DeepUAV successfully gathers a substantial amount of the current data consistently while mitigating the risk of energy depletion in SNs and the UAV.

Data From the Drain: A Sensor Framework That Captures Multiple Drivers of Chronic Coastal Floods

AbstractTide gauge water levels are commonly used as a proxy for flood incidence on land. These proxies are useful for projecting how sea‐level rise (SLR) will increase the frequency of coastal flooding. However, tide gauges do not account for land‐based sources of coastal flooding and therefore flood thresholds and the proxies derived from them likely underestimate the current and future frequency of coastal flooding. Here we present a new sensor framework for measuring the incidence of coastal floods that captures both subterranean and land‐based contributions to flooding. The low‐cost, open‐source sensor framework consists of a storm drain water level sensor, roadway camera, and wireless gateway that transmit data in real‐time. During 5 months of deployment in the Town of Beaufort, North Carolina, 24 flood events were recorded. Twenty‐five percent of those events were driven by land‐based sources—rainfall, combined with moderate high tides and reduced capacity in storm drains. Consequently, we find that flood frequency is higher than that suggested by proxies that rely exclusively on tide gauge water levels for determining flood incidence. This finding likely extends to other locations where stormwater networks are at a reduced drainage capacity due to SLR. Our results highlight the benefits of instrumenting stormwater networks directly to capture multiple drivers of coastal flooding. More accurate estimates of the frequency and drivers of floods in low‐lying coastal communities can enable the development of more effective long‐term adaptation strategies.

Application of wireless measurement technology in hydraulic turbine test

At present, the measurement of internal characteristics of hydraulic machinery runner (blade pressure pulsation, pressure field and dynamic stress) and blade torque is difficult to be realized by the existing wired measurement methods due to the measurement object is a high-speed rotating part. This paper will introduce the system composition and application in hydraulic machinery of the wireless measurement technology one by one. In the measurement of model hydraulic machinery, it is mainly used to measure the rotating part. The sensors work in water, including measuring the internal characteristics of the runner (blade pressure pulsation, pressure field and dynamic stress) and blade torque. The wireless measurement technology that is by laying the corresponding measurement unit at the measured part, the signal sensed by the sensor is collected and stored by the node, and then wirelessly transmitted through the node, and the data is received through the wireless gateway and enters the computer acquisition system.

Development of a Real-Time Monitoring and Calculation Method for TBM Disc-Cutter’s Cutting Force in Complex Ground

Abstract Cutting force is an essential parameter of the operating state of tunneling boring machines. In this study, a real-time cutting force monitoring method is proposed for widely used disc-cutters. A microcylindrical strain gauge is embedded in predrilled small boreholes in the bottom and side surface of the two C-shaped cushion blocks on the cutter saddle. The strain gauges are protected by a glue seal, and the sensor leads are protected using a groove and covered by wear-resistant steel. The strain is measured using a wireless strain node and transmitted from the strain node to the wireless gateway connected to a computer. Then, the strain-force relationship of the cushion block is fitted using a laboratory static calibration test. The load on the cushion block is calculated based on the measured cushion block strain. Subsequently, considering the cutter system’s vibration, a multi-degree-of-freedom coupling vibration differential equation of the cutter system is established. The mass matrix, stiffness matrix, and damping matrix of the cutter system are also determined. Finally, a Wilson-θ inverse analysis method is put forward to calculate the cutter’s external load. The developed real-time cutting force monitoring method will not affect cutter replacement, and the cushion block equipped with sensors can be reused. The cutting force identification method, which considers the cutter system vibration, is rigorous in theory, and a useful numerical inverse analysis calculation method is provided.

An in-Depth Study of Smart Agriculture Based on Internet of Things and Wireless Sensor Networks

Most governments monitor and prioritize agriculture. Subsidies and loans to farmers to promote food production are common in many countries. They are pushing farmers to employ modern agrarian technology to boost grain quality and farming. Smart farming relies on Wireless Sensor Networks and the Internet of Things. Using the above technology, farmers may monitor their property remotely and manage their farms at any time sensors nodes installed on fields capture agricultural growth data using GPS. Sensor nodes collect data on soil nutrient levels, temperature, and humidity. The sensor delivers data to a wireless gateway, which sends it to a remote server. Researchers and scientists have been working hard to improve farmers' productivity, quantity, and quality. This study examines the impact of new technologies and sensors used in smart farming on food security and how such devices are transforming agricultural sectors to meet rising population demands.

Early faults diagnosis and severity assessment of rolling element bearings on wireless signal transfer

Machine condition monitoring in remote locations and harsh environment where network infrastructure is not feasible, or hardwired network connectivity is not possible, wireless communications provides an alternative which also offer installation cost savings, improve reliability and quicker deployment. This paper describes the implementation of wireless sensor network (WSN) for early fault diagnosis of rolling element bearings based on signal autocorrelation technique. A low-power 2.4 GHz wireless HART transceiver, a low-cost wireless vibration transmitter, 26.76 mv/g accelerometers and a 1420 wireless gateway with AMS software was implemented. The research describes the methodology of acquiring peak values data in high frequency region. The noise was averaged out by applying four-time averaging and natural frequencies or fault frequencies of bearing elements was captured. The experimental results show that the signal autocorrelation algorithm can successfully diagnose the roller bearing faults at early stage on wireless signal transfer. As the raw data was processed before wireless transmission on analyzing unit and spectrum was transferred in JPG format on display unit, minimum power consumption has been noted. The technique provided a better alternative of wired system for real time condition monitoring of roller bearings in rotating equipment installed in remote area.

RETRACTED ARTICLE: IoT-based smart environment using intelligent intrusion detection system

One of the most basic characteristic features of every smart device in a network based on the Internet of Things (IoT) is to gather a larger set of data that has been created and then transfer the gathered data to the destination/receiver server through the internet. Thus, IoT-based networks are most vulnerable to simple or complex attacks that need to be identified in the early stage of data transmission for saving the network from these malicious attacks. The chief goal of the proposed work is to design and form the intelligent intrusion detection system (I-IDS) using the machine learning models such that the attacks can be identified in the IoT network. The model is built considering the normal and malicious attacks on the data that are generated in IoT smart environment. To simulate such a model, a testbed is built where a wireless router, a DHT11 sensor, and a node MCU are being used during the design phase. An attacker or adversarial system is built to perform poisoning and sniffing attacks using a laptop system. The node captures the sensor values and transmits the data to the ThinkSpeak platform, during the normal phase via the wireless gateway, and in the attack phase, the malicious attacker interprets the data, modifies it while transmitting from node to the ThinkSpeak server. Thus, the attack called Man-In-The-Middle (MITM) is performed and classified as abnormal data. Various machine learning algorithms are performed on the data, and finally, the results obtained using a probabilistic model called as Markov model have a high performance evaluated based on the I-IDS IoT network. The results obtained during the experimental analysis show that the Markov model has obtained a 100% detection rate and 19% of false alarm rate (FAR) with high precision and low error rate. The algorithms such as naïve Bayes classifier, support vector machine (SVM), decision tree, and Adaboost are considered in comparison with the Markov model. The optimal solution is obtained concerning other evaluation metrics like sensitivity, F1, and true-positive rate (TPR). Therefore, the integrated network of IoT-WSN with its performance metrics is tabulated to show the potentials of securing a network system. Additionally, the proposed work gives a high level of security for IoT smart environment as compared with the other machine learning algorithms using the novel technique of intelligent IDS.

Utility of Multi Wireless Gateway in Advanced Touchless Healthcare Management

In these days of u-healthcare, for convenient monitoring of biological parameters, the wireless communication technique is necessary. There are some standard techniques such as Bluetooth, Wireless LAN, ZigBee, etc. used in the recording of patient’s details. The techniques were tested for Patient details networking and summarize its advantages and the disadvantages. As a result, the ZigBee radio is used as sensor network of patient’s in the hospital. This patient monitoring system would have been tested which has several biological parameters. Especially, this system has ability of patient’s parameter monitoring in the hospital. In this paper in order to record patient’s details repeatedly RFID tags are used which shows complete profile of the patients biological parameters. Whenever patients expose their cards in a RFID field, complete details are displayed in a computer.

Research on Intelligent Home Design of Internet of Things Based on ZIGBEE

With the rapid development of information technology, improving the intelligent level of family life and modern life style is the trend of future development. Based on the analysis of the development of smart home at home and abroad, a smart home system is designed by combining ZigBee wireless sensor network, gateway technology and mobile terminal remote control app. Firstly, the development and relating technologies of ZigBee are discussed. Secondly, the system overall architecture and data outlier analysis are carried out. Thirdly, the routing algorithm of ZigBee is improved based on neighbour table, and corresponding mathematical model is designed. Fourthly, the location algorithm of ZigBee is improved based on RSSI location algorithm and DV-Hop algorithm. Finally, the system performance is tested based on simulation analysis, results show that the proposed intelligent home system has better performance.

Sum-rate maximization and data delivery for wireless seismic acquisition

Traditional seismic acquisition systems suffer from a number of difficulties related to telemetry cables that are used as a means of data transmission. Transforming the traditional seismic acquisition system to a wireless system has been considered as a potential solution to most of these difficulties. The wireless seismic acquisition system has to serve a huge aggregate data rate requirement as is usually the case in a large wireless sensor network. This paper considers the wireless acquisition system, and studies the maximum achievable transmission data rates from the geophones to the wireless gateways. Successive interference cancellation decoding is assumed to be used at the gateway nodes. We consider the problem of sum-rate maximization by optimizing the decoding process at each gateway node. The optimization searches for optimal decoding set at each gateway, i.e. which group of geophones will be decoded at each gateway. Various integer programming algorithms are proposed for solving the maximization problem. These optimization algorithms are simulated and compared among each other, where it is shown that the ant system algorithm achieves the highest sum-rate with lower computational complexity compared to other algorithms. Furthermore, the data delivery from the gateways to the data center is also considered. In this stage, two gateways with different buffer sizes are studied. For small-size buffers, two optimization problems are identified and solved. The first problem considers the minimization of the total power of the gateways, and the second problem considers power fairness between the gateways. For large-size buffers, the problem of maximizing the weighted sum rate of the gateways is solved.

CMCVT: A Concurrent Multi-Channel Virtual Transceiver

State-of-the-art wireless Gateways (GW) used in Internet of Things (IoT) offer a single channel radio link, which limits the capabilities of the IoT network controlled by the GW, as the GW can only use a single channel at a time to communicate with the end-device(s). The quality of service (e.g., aggregate throughput, latency) offered by a single channel GW could be substantially improved by employing a multi-channel transceiver, which is capable of transmitting/receiving data on different radio channels simultaneously, particularly for larger wireless networks. However, current solutions available in both research and commercial communities only offer multi-channel receiver capabilities, and do not incorporate the multi-channel transmitter part. In addition, in terms of implementation, these multi-channel receivers duplicate single-channel hardware functionality. In this paper, for the first time, a novel concurrent multi-channel virtual transceiver is introduced. The virtual transceiver offers multi-channel capabilities and uses the same single-hardware hardware implementation for the Physical (PHY) layer by employing the virtualization technique. This new virtual transceiver concept is demonstrated for an IEEE 802.15.4 based 8 × 8 channel transceiver, implemented on an Field Programmable Gate Array (FPGA) of a modern Software Defined Radio and is compared with the existing duplication approach. The duplication approach consumes 9008 LUTs, and 12120 FFs, whereas the proposed approach occupies only 2959 LUTs and 2105 FFs, saving 67.15% LUTs and 82.63% FFs in comparison with the duplication approach. The experimental results reveal that the virtual transceiver provides the same performance (e.g., receiver sensitivity of −98.5dBm) as the transceiver achieved by duplicating the PHY layers but consumes much less hardware resources.

A Visitor Assistance System Based on LoRa for Nature Forest Parks

Ecotourism activities are attracting more people each day, including national forest parks. Unfortunately, the number of incidents involving visitors to natural parks grows at the same pace. Among the most prevalent risks inside forests are getting lost and the occurrence of natural disasters. In this work, we propose a system for monitoring and assisting visitors of forest parks, based on a low power wide range wireless network, LoRa. The proposed visitor assisting system is composed of mobile terminals that communicate between them and with fixed infrastructure, using a protocol designed for exchanging visitor locations data. The infrastructure consists of wireless gateways distributed on the trails, the totems. User terminals, the mobile nodes, work collaboratively through a Delay and Disruption Tolerant Network (DTN), to cope with the possibility that the gateway infrastructure does not cover the whole trail. In addition to improvements and gains for minimizing risks, the proposal also brings contributions to the preservation of the environment, raising awareness of the influence of human presence in the natural environment and to the development of environmental education actions.

Building a Intrusion Detection System for IoT Environment using Machine Learning Techniques

Abstract The most basic feature of every smart device or endpoint device in IoT is to collect the large amount of data that is being generated and direct it to a destination server via the Internet. IoT network is vulnerable to attacks and identification of these malicious behaviours at an early stage can save the data from attacks. The main objective of this work is to build machine learning models to identify attacks in IoT network. To build a model, normal and attack data needs to be generated from the IoT environment. A test bed is build to simulate the IoT environment using Node MCU ESP8266, DHT11 sensor and wireless router. An adversarial system is build using a laptop system which performs actions of sniffing and poisoning attacks. Data captured from the sensors were temperature, humidity and due-point which are transmitted to ThinkSpeak platform using wireless gateway. In the normal phase, sensor values is captured by Node MCU and transmitted to Think Speak server which are stored and labelled as normal data. In the attacking phase, from an adversarial system, the attacker secretly intercepts the data, modifies the data when it is transmitted between the Node MCU and Think Speak server. In the attacking phase, Man in the Middle attack is performed in the network using ARP Poisoning and the data captured is labelled as attack data. Machine learning classifiers such as Naive Bayes, SVM, decision tree, Adaboost are built to categorize data into normal and attack classes.

Cross-Layer Design and Analysis of Wireless Geophone Networks Utilizing TV White Space

Traditional seismic data acquisition systems used for surveying during the exploration of oil and gas rely on cables between geophones and the data collection center. Despite the fact that cable-based systems provide reliable seismic data transfer, their deployment and maintenance costs increase substantially as the survey area increases in scale. Therefore, a three layer wireless network architecture is proposed in this work, which consists of wireless geophones (WG) and a data center with an intermediate wireless gateway node (WGN). This paper investigates the aggregate data throughput, transmission time, and energy consumption from WGs to the WGN in a wireless geophone network architecture based on the IEEE 802.11af standard. This standard is considered in order to have the maximum possible range and low power consumption due to operating in TV bands. Analytical expressions of the aforementioned quantities are derived using Markov chain models. Two Markov models are considered for this purpose: one for modeling the access method that allows multiple WGs to connect to a WGN and the other for representing a buffer in a WG. Since seismic data is recorded at regular intervals, arrivals of data packets in the buffer of the WG is deterministic. On the other hand, departure is random due to the multiple access method. Hence, in this work D/M/1/B queue is used for the first time to model the buffer in a wireless geophone. Furthermore, the physical layer constraints are also taken into account together with proper wireless path-loss channel models. The results obtained are useful for designing such wireless seismic networks without extensive simulations. In particular, the proposed joint medium access control, physical layer, and D/M/1/B model enables us to optimize the required number of WGNs. Finally, sectoring is also introduced in order to minimize the total number of WGNs needed to cover the whole surveying area.

Electronic Devices Monitoring based Wireless Gateway Network using Cisco Packet Tracer

Electronic Devices Monitoring based Wireless Gateway Network using Cisco Packet Tracer

Data Provenance for IoT With Light Weight Authentication and Privacy Preservation

The Internet of Things (IoT) engulfs a large number of interconnected heterogeneous devices from a wide range of pervasive application areas including health-care systems, energy management, environmental monitoring, and home and commercial automation. Although IoT is considered an enabling technology for a variety of services, it also raises many security and privacy concerns. This article focuses on developing secure protocols for data provenance with authentication and privacy preservation in IoT systems. Protocols for two scenarios are presented, one when an IoT device is directly connected to a wireless gateway and the other when an IoT device is indirectly connected to the wireless gateway through multiple hops of other IoT devices. The proposed protocols use physically unclonable functions along with wireless link fingerprints derived from the wireless channel characteristics between two communicating entities. This results in protocols which are not only efficient in terms of computational complexity and energy requirements but are also safe against various types of attacks including physical and cloning attacks. Experimental results show that in comparison to existing protocols, the proposed protocols are up to 100% more accurate in detecting attacks on data provenance and can save up to 83.8% and 73.5% energy consumption for the IoT devices in terms of CPU and radio energy, respectively.

Dual‐collaborative DoS/DDoS mitigation approach in information‐centric mobile Internet

SummaryThe amount of wireless traffic is increasing at an overwhelming speed. Information‐centric networking (ICN) has been proposed as a promising Future Internet Architecture, which can reduce network traffic by putting data objects toward the edge. It is expected that in information‐centric mobile Internet (ICMI), the wireless traffic can be significantly reduced. Yet, DoS/DDoS attack becomes a critical issue in ICMI by causing wireless gateway blockade. To tackle the problem, we propose a dual‐collaborative DoS/DDoS mitigation approach (DCMA) and advanced DCMA to protect wireless gateways. In the algorithm, the attackers' visiting information including international mobile equipment identity (IMEI) and data object name (DON) are analyzed jointly to accurately identify potential attackers through the collaboration between the Internet and mobile network. In addition, the attacker's behaviors are analyzed centrally, and security strategies are applied distributively throughout wireless edge through the collaboration between wireless core network (CN) and radio access network (RAN). Extensive simulations are performed to verify the effectiveness of the proposed algorithms. The results demonstrate that advanced DCMA can achieve high DDoS and attacker detection probability and small false positive probability.

Development of a Wireless Gateway for Industrial Internet of Things Applications

Industry 4.0 is a new concept representing the evolution of the current production systems through the convergence of new technologies of industrial automation and information systems. The Industrial Internet of Things (IIoT) stands out for the communication among equipment and systems, offering to users a variety of useful information for the management of improvement of production systems. This paper presents the development of a wireless gateway for IIoT applications. This IIoT gateway is based on open source solutions and enables the programming, network communication and supervision of the industrial equipment. The communication protocols supported by the gateway are: Modbus TCP/IP, MQTT and CoAP for connection between the remote modules and the gateway and HTTP using the REST standard with JSON format for external communication with the gateway. An innovation and differential of the gateway was adding the OpenPLC project in order to enable the programming and automation of industrial processes according to the IEC 61131-3. In addition, the gateway stores process information and makes it available online and accessible in real-time to any point connected to the network and/or the Internet. Several operation tests performed validated the development and demonstrated the efficacy of the gateway.

On-site Evaluation of Rehabilitation Patients Monitoring System Using Distributed Wireless Gateways.

This paper presents a hands-free monitoring system for rehabilitation patients that uses wireless gateways to fully cover the floor of an inpatient ward. For stroke rehabilitation, 24-hour monitoring is recommended. Low-power wireless such as Bluetooth Low Energy (BLE) is suitable for this purpose because of its long battery life. However, most systems require smartphones or tablet computers to acquire patient data due to BLE's short communication range. Instead of using smartphones, we installed around fifty BLE gateways to implement a hands-free data acquisition system. The system was evaluated both quantitatively and qualitatively. The data acquisition rate of the system was found to be over 90% through 24-hour patient monitoring, which is almost the same as that for systems using smartphones. Questionnaires about usability administered to both medical staff and patients suggested that they felt the smartphone-less system was more comfortable than the smartphone system. These results suggest the possibility of using such a distributed data acquisition system in real medical wards and its benefits.

The Development and Field Evaluation of an IoT System of Low-Power Vibration for Bridge Health Monitoring.

Bridge safety is important for the safety of vehicles and pedestrians. This paper presents a study on the development of a low-power wireless acceleration sensor and deployment of the sensors on a wireless gateway and cloud platform following the Internet of Things (IoT) protocols for bridge monitoring. The entire system was validated in a field test on the Chijing bridge in Shanghai. Field evaluations indicated that the developed IoT bridge monitoring system could achieve the functions of real-time data acquisition, transmission, storage and analytical processing to synthesize safety information of the bridge. The demonstrated system was promising as a complete, practical, readily available, low-cost IoT system for bridge health monitoring.