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In future next Generation wireless networks, it is expected to have multi-mode wireless interface devices with common IP core communication. The user will be having multiple option of radio access technology (RAT) for data and voice service. This multi-mode provides the terminal seamless mobility across the heterogeneous wireless network. Mobile terminals transferring their communication sessions from one RAT to other, such transferring ongoing call process is known as vertical handover. With the rise in popularity of multimode mobile devices, switching between networks will be in high demand for users to move seamlessly through the network, either because users were moving away from an access point or because the network currently does not provide quality. service (QoS), but in both situations, a better network should be available, so a good network selection algorithm should take into account the possibility of multiple users performing a handover simultaneously in the same area. The objectives of this paper are to develop a handover mechanism that Provides good quality of service to the end user.

This paper describes a wearable, open-source wrist temperature monitoring system that enables the reliable identification of slowly-varying skin temperature patterns that may be indicative of infections. The hardware platform uses a Bluetooth Low Energy (BLE) wireless interface and includes three skin temperature sensors, a thermally-isolated ambient temperature sensor, an inertial measurement unit (IMU), and a Galvanic skin response (GSR) sensor. A template-matching algorithm is used to detect weak but long-lived anomalous temperature patterns that deviate from the normal circadian rhythm are thus may be driven by infections. Experimental and simulation results confirm that small temperature anomalies (peak value < 0.4°C) extending over 2-3 weeks can be detected with a total error rate < 10%.

Reconfigurable Wireless Sensor Network (RWSN) schedules a set of devices with reconfigurable wireless interface to accomplish different data collection plans in a cost-effective way. AI technologies are applied to optimize decision making for high-level network reconfiguration. Besides, AI based data mining tools are exploited by third parities to extract useful information underlying raw data. This leads to the emergence of AI enabled RWSN. We further study a data trading market to provide the data-centric environment for large-scale applications of AI enabled RWSN. A network operator employs the devices to gather environmental data, and sells the collected data to interested third parities as data consumers. After that, two-level optimizations are performed to ensure efficient data trading. In data collection, a contract based incentive mechanism is presented for the network operator to stimulate the devices and simultaneously achieve the contractor's goal subject to feasible constraints. In data selling, a non-cooperative game is formulated among multiple data consumers. They balance the data demand since the final data price is correlated with the total data demand. Nash equilibrium is analyzed and solved under different scenarios. Finally, numerical results are provided to demonstrate the effectiveness of our scheme.

The recent development of wireless Network-on-Chip (WiNoC) by introducing wireless interface in traditional wired NoC has significantly increased the performance of NoC systems with higher bandwidth and low latency on-chip communication. However, the integration of more components (e.g., antenna and transceiver) on the chip also increases system complexity and makes it more susceptible to various failures. In this paper, we propose a run-time fault diagnosis mechanism based on neural network (NN) techniques, where both fully-connected (FC) and convolutional neural networks (CNN) are considered. For NoC with 2-D mesh topology that incorporates both wired and wireless interfaces, the FC and CNN neural networks for fault diagnosis and detection are presented. The NN models can be trained offline with collected traffic data from partially failed NoC with various faulty components. Then, at run-time, the NN models can be deployed on certain tiles in the NoC to detect and locate the faulty components using the run-time traffic data. Based on simulated traffic data, we have evaluated the proposed NN-based mechanism under different fault scenarios (e.g., type, location and number of faulty components). The results show that, CNN models outperform FC neural networks with higher fault diagnosis rates. CNN can successfully identify up to 81.2% faults when there is only one faulty component on the NoC with different traffic patterns. The accuracy decreases when there are more faulty components and higher traffic loads.

Electric vehicles (EVs) that offer grid services using the vehicle-to-grid (V2G) concept essentially require an interface that allows for directional power flow. This article presents a wireless bidirectional grid power interface for EVs that facilitate power flow between the grid, EV, and homes with nonlinear loads. The proposed wireless vehicle-to-grid-to-home power interface (WVGH-PI) uses the grid-side low frequency to dc converter, used in typical wireless bidirectional chargers only to facilitate the two-way energy flow, to improve the power quality by compensating for the harmonic power and reactive power of nonlinear household loads. To improve the overall efficiency of the interface, an adaptive dc-link voltage controller is also proposed. Operation of the proposed wireless interface is investigated under dynamic conditions and in different modes. The simulation and experimental results obtained from a 1-kW prototype are presented, benchmarking against conventional control, to demonstrate the validity of the proposed concept.

To cope with the shortage of available licensed spectrum, 4th Generation Long Term Evolution (4G LTE) is expected to be deployed also in the unlicensed spectrum. This raises the problem of the coexistence of multiple operators. Obviously, a Software Defined Networking (SDN) based control approach can utilize the radio bandwidth by coordinating between multiple LTE-Unlicensed (LTE-U) operators. Within SDN control plane, there is a well-known issue namely the Controller Placement Problem (CPP) which has a major impact on the efficiency of the control plane. This paper addresses the Wireless Controller Placement Problem (WCPP) when the SouthBound interface (SBi) is based on 4G LTE unlicensed. The proposed solution improves the throughput, link failure probability and the transparency on the SBi from concurrent transmissions on the control plane. Two heuristic solutions are considered, one is a simulated annealing based and the other is a ray-shooting based. The simulation results show that they are fast and efficient and the ray-shooting based heuristic out-performs the simulated annealing based heuristic. In addition, it is shown that the transparency improves in bigger networks.

A two-channel real-time intelligent electroencephalography (EEG) measurement system with electrical and optical stimulations is presented for seizure detection and suppression. Based on software control through a wireless interface, this system provides closed- and open-loop feedback control with programmable waveform for electrical and optical stimulations. Matlab graphical user interface is used to monitor the intracranial EEG, perform the algorithm for seizure detection, and adjust the required intensity, frequency, duty cycle, and duration of electrical and optical stimulations. The whole hardware device is embedded on a printed circuit board with the size of 27.3 mm $\times23.6$ mm. C57BL/6 mice with Thy1-ChR2-YFP gene transfer and drug-induced seizure are used to demonstrate epileptic seizure suppression according to electrical and optogenetic stimulation in the proposed wireless EEG measurement system.

The increase in the demand for electricity in the last decades has forced consumers to adopt strong rationing measures. However, these actions, often evidenced in small intuitive ways of reducing consumption, are not enough to improve energy efficiency. The user’s awareness needs to be accompanied by increasingly interactive and autonomous tools that allow them to know the true dimension of the financial impact on the inadequate use of domestic electrical and electronic equipment. In this sense, a wireless electronic device capable of noninvasively acquiring signals from household mains installed in a residence was developed so that the system can identify the connected equipment in the electrical network and how much it is contributing to power consumption. After the measurement by the developed device, your performance was compared with two energy analyzers in the market where the loads were disaggregated and classified with the Pearson’s correlation and using an ANN (artificial neural network). Analysis of the test results revealed that the ANN was more efficient in classifying loads, in comparison with the Pearson’s method, with 91% accuracy of the device proposed in this work.

A Mobile Ad-hoc Network (MANET) is a group of nodes connected via ad-hoc fashion for communicating with each other through wireless interface. The communication among the nodes in such network take place by using multi-hop in the absence of fixed infrastructure. TCP faces some hurdles and complexities in multi-hop ad-hoc networks particularly congestion and route failures. The incompatibility between the MAC and TCP are previously noticed by the research community. This research study focuses on the impact of MAC layer contention window on TCP in MANET by using variation in network density and velocity of nodes respectively. Simulation has been carried out to quantify and analyze the impact of Contention Window (CW) sizes that affects the performance of TCP by using NS-2 simulator. The impact of CW is investigated on TCP in multi-hop networks by means of performance evaluation parameters i.e. average delay, average packet drops and average throughput.

In the past few years it has been demonstrated that electroencephalography (EEG) can be recorded from inside the ear (in-ear EEG). To open the door to low-profile earpieces as wearable brain-computer interfaces (BCIs), this work presents a practical in-ear EEG device based on multiple dry electrodes, a user-generic design, and a lightweight wireless interface for streaming data and device programming. The earpiece is designed for improved ear canal contact across a wide population of users and is fabricated in a low-cost and scalable manufacturing process based on standard techniques such as vacuum forming, plasma-treatment, and spray coating. A 2.5 × 2.5 cm2 wireless recording module is designed to record and stream data wirelessly to a host computer. Performance was evaluated on three human subjects over three months and compared with clinical-grade wet scalp EEG recordings. Recordings of spontaneous and evoked physiological signals, eye-blinks, alpha rhythm, and the auditory steady-state response (ASSR), are presented. This is the first wireless in-ear EEG to our knowledge to incorporate a dry multielectrode, user-generic design. The user-generic ear EEG recorded a mean alpha modulation of 2.17, outperforming the state-of-the-art in dry electrode in-ear EEG systems.

In recent years, advanced driver assistance systems (ADASs) have been used to improve the safety of vehicles by either providing additional information to the driver or by taking over complete control. The majority of ADASs currently being utilised run entirely on the vehicle, only having access to information provided by the sensors that are onboard the vehicle itself. Part of the next step in the evolution of ADAS is to incorporate information from other offsite sensors or obtain control inputs from infrastructure which can coordinate multiple vehicles simultaneously via a wireless interface. Wireless communication is inherently delayed and prone to dropped packets. This study looks at the effect of transport latencies and dropped packets on an off-site autoregressive steering controller supplying direct steering inputs to a vehicle. A fully non-linear vehicle simulation model is used to test the effect of delaying steering inputs and dropped packets to test the stability of the controller. The study shows that at dropped packet percentages of up to 40% adequate vehicle control is maintained, while transport latencies of up to 100 ms allow for moderately accurate vehicle control.

The development of a low-cost solution for the connection of wireless sensor nodes to the Internet is presented. The solution has the additional benefit of extremely low power consumption and hence very long battery life and low maintenance cost. The core of the solution is the Atmel ATtiny series of wireless transceivers and the designs of minimised printed circuit boards for three versions of the node are presented. To provide the fixed node at minimum cost, the Raspberry Pi microcomputer was used, attached to the Nordic Semiconductor nRF24L01+ transceiver module. Software to implement the system in each of the nodes was developed from zero-cost sources, the software being tailored for the particular application and devices selected. A World Wide Web interface for the Raspberry Pi was created, having an intuitive display and offering functionalities relevant for general automation tasks, data display and manual control, in conjunction with wirelessly connected clients. The Web interface can serve as the basis for a home automation system, a topic which is becoming more and more important and popular nowadays, but industrial applications are equally feasible.

Device-free passive wireless indoor localization is attracting great interest in recent years due to the widespread deployment of Wi-Fi devices and the numerous location-based services requirements. In this paper, we propose DFPhaseFL, the first device-free fingerprinting indoor localization system that purely uses CSI phase information. It utilizes the CSI phase information extracted from simply a single link to estimate the location of the target, neither requiring the target to wear any electronic equipment nor deploying a large number of access points and monitor devices. In DFPhaseFL, the raw CSI phases are extracted from the CSI measurements through the three antennas of the Intel WiFi Link 5300 wireless Network Interface Card (IWL 5300 NIC) firstly. Then, linear transformation and noise filtering are applied to acquire the calibrated CSI phases. Through experimental observations, we find that the calibrated CSI phase owns an unpredictable characteristic over time. Thus, it cannot be directly applied as a fingerprint. To this end, a transfer deep supervised neural network method combining deep neural network and transfer learning is proposed to obtain feature representations with both transferability and discriminability as fingerprints. Then, the DFPhaseFL system uses the SVM algorithm to obtain the estimation of the target location online. Experiment results demonstrate that the DFPhaseFL owns a better estimation precision compared with the other state of art, and maintain a stable localization accuracy for a long time without reacquiring the fingerprint database.

Healthcare systems have been an important part of the research on consumer electronics in recent years. To be a mass-market product, a healthcare system is combined with a home control system. In this article, an ultra-high-frequency radio-frequency-identification (UHF RFID) wireless interface is built and implemented for the bio-signal monitoring of the healthcare system. This interface is composed of a digital baseband processor with an application specific integrated circuit (ASIC) for the RFID reader and tag. All functions are implemented to fit the requirement of electronic product code class 1 generation 2 protocol, such as cyclic redundancy check/verify, pulse interval encoding, and bi-phase space coding. The system platform was built to obtain bio-signals, which can demonstrate the hand-shaking stage and communication between the reader and tag at the same time. The tag was fabricated under the 180-nm standard CMOS process with the average power consumption of only 73.62 $\mu \text{W}$ . The reader was implemented by a field programmable gate array in the system. The power consumption of the entire system combined with those in our previous works, which include analog front-end and radio-frequency front-end, is considered. It achieves 75 $\mu \text{W}$ , which is lower than those achieved with the existing state-of-the-art wireless interface. Moreover, the wearable device with ASICs is proposed to feature on relative low power and small size. Thus, it is more suitable for consumer electronics.

The indoor positioning method based on received signal strength indication (RSSI) ranging is a lack of systematic quantitative research on the factors affecting the characteristics of indoor RSSI, which affect the accuracy of positioning. This paper quantitatively analyzes the characteristics of the 2.4 GHz RSSI collected in indoor scenes from the following four aspects: antenna orientation of the receiver, type of wireless network interface card (NIC) of the receiver, time period of the data measurement and height difference between the transmitting and receiving antenna. The experimental results show that: (i) the RSSI value measured is the strongest when the antenna of the receiver is vertically oriented to the antenna of the transmitter, while the weakest when the antenna is vertically back-facing and the difference between the strongest signal and the weakest signal is 20-25% at the same test point; (ii) the wider the measurement range of NIC, the more conducive to data collection; (iii) the distribution of RSSI signals generated by an access point at a fixed position is inconsistent with time; (iv) when the height of receiving antenna is 0.5 m different from each other, the path loss index of ranging model produces a deviation of about 10%.

In this paper, we analyze a queueing system under the dyadic server control, workload control and delivery deadlines of data blocks. From the viewpoint of efficient power management for the wireless interface of a smart mobile device, we first focus on deriving the mean length of an arbitrary cycle time and then investigate the mean energy expenditure during the cycle. Some numerical examples are shown with respect to several control parameters. We conduct simulations to evaluate the proposed analytic energy consumption models. Experiments are also performed by implementing a test program on an off-the-shelf smartphone. Our results can serve as quantitative guidelines for the efficient power management of wireless interfaces in mobile devices.

This paper presents a wearable multi-biosignal wireless interface for sleep analysis. It enables comfortable sleep monitoring with direct sleep-stage classification capability while conventional analytic interfaces including the Polysomnography (PSG) require complex post-processing analyses based on heavy raw data, need expert supervision for measurements, or do not provide comfortable fit for long-time wearing. The proposed multi-biosignal interface consists of electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG). A readout integrated circuit (ROIC) is designed to collect three kinds of bio-potential signals through four internal readout channels, where their analog feature extraction circuits are included together to provide sleep-stage classification directly. The designed multi-biosignal sensing ROIC is fabricated in a 180-nm complementary metal-oxide-semiconductor (CMOS) process. For system-level verification, its low-power headband-style analytic device is implemented for wearable sleep monitoring, where the direct sleep-stage classification is performed based on a decision tree algorithm. It is functionally verified by comparison experiments with post-processing analysis results from the OpenBCI module, whose sleep-stage detection shows reasonable correlation of 74% for four sleep stages.

Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.

The energy consumption of wireless interface is critical to power-constrained mobile devices. To improve energy efficiency for WLAN stations, power saving mode (PSM) is proposed, to manage the time spent in idle listening (IL) state. The hurdle is that the receiver has no knowledge about when the pending data will arrive under end-to-end communication protocols (TCP/IP), making each station spend enormous time in IL to wait for the pending data. To overcome this limitation, in this paper, we propose a named data networking (NDN) enabled PSM, namely, NDN-PSM, which leverages NDN communication architecture to cut down unnecessary IL time. In particular, we devise two new power states in NDN-PSM , i.e., light doze and deep doze, to precisely map to the underlying data arriving states. The inherent receiver-driven pattern of NDN can effectively drive the stations to the deep doze state for power saving, and to light doze state for timely data reception. Considering the IL time waste during channel contention, we further design a channel contention control mechanism in NDN-PSM , in which stations will switch to the light doze state if the channel is perceived to be busy. The power consumption model of the proposed NDN-PSM is theoretically analyzed and verified via numerical results. At last, we implement NDN-PSM in NS-3 by adopting the ndnSIM module and conduct extensive simulations to demonstrate the efficacy of NDN-PSM . Specifically, compared to the existing PSM mechanism, NDN-PSM reduces 56% power consumption by cutting down unnecessary IL time, and meanwhile enables low-delay transmission.

Monitoring WiFi networks is essential to gain insight into the network operation and develop methods capable of reacting to network dynamics. However, research and development in this field are hindered because there is a lack of a framework that can be easily extended to collect various types of monitoring data from the WiFi stack. In this paper, we propose FLIP, a framework for leveraging eBPF to augment WiFi access points and investigate the performance of WiFi networks. Using this framework, we focus on two important aspects of monitoring the WiFi stack. First, considering the high delay experienced by packets at access points, we show how switching packets from the wired interface to the wireless interface can be monitored and timestamped accurately at each step. We build a testbed using FLIP access points and investigate the factors affecting packet delay experienced in access points. Second, we present a novel approach that allows access points to track the duty-cycling pattern and energy consumption of their associated stations accurately and without the need for any external energy measurement tools. We validate the high energy measurement accuracy of FLIP by empirical experiments and comparisons against a commercial tool.

In this paper, we discuss utilizing device-to-device communication, i.e., sidelink, with 5G URLLC for meeting the stringent latency/reliability requirements in certain industrial IoT scenarios, e.g., factory automation. In particular, we describe various aspects for one specific use-case of wireless controller: different architectures for combining gNB-UE links and UE-UE sidelinks; enabling enhancements at the physical, medium-access, and upper layers; some results of performance evaluation; and a prototype.

Modern vehicle is considered as a system vulnerable to attacks because it is connected to the outside world via a wireless interface. Although, connectivity provides more convenience and features to the passengers, however, it also becomes a pathway for the attackers targeting in-vehicle networks. Research in vehicle security is getting attention as in-vehicle attacks can impact human life safety as modern vehicle is connected to the outside world. Controller area network (CAN) is used as a legacy protocol for in-vehicle communication, However, CAN suffers from vulnerabilities due to lack of authentication, as the information about sender is missing in CAN message. In this paper, a new CAN intrusion detection system (IDS) is proposed, the CAN messages are converted to temporal graphs and CAN intrusion is detected using machine learning algorithms. Seven graph-based properties are extracted and used as features for detecting intrusions utilizing two machine learning algorithms which are support vector machine (SVM) & k-nearest neighbors (KNN). The performance of the IDS was evaluated over three CAN bus attacks are denial of service (DoS), fuzzy & spoofing attacks on real vehicular CAN bus dataset. The experimental results showed that using graph-based features, an accuracy of 97.92% & 97.99% was achieved using SVM & KNN algorithms respectively, which is better than using traditional machine learning CAN bus features.

Disinfecting a closed space is a widely discussed topic since the spread of coronavirus. Different methods like chemicals in liquids and gases are used to eliminate pathogens. But these methods would cause environmental damage, which would become another problem for humanity. We developed a robot which uses ultraviolet-C (UV-C) technology for surface disinfection, particularly room in houses, offices, hospitals etc. UV-C radiation is effective against coronavirus and is extremely effective in breaking down the DNA of microorganisms which means they cannot replicate and cause disease. The teleoperated robot is capable of 360-degree disinfection with three UV-C lamps used. It is controlled using an Android app through Bluetooth wireless interface. Due to wireless control, the operator can safely operate the robot from outside the room. The robot is also equipped with a self-timer for turning off the UV-C lamps automatically. The robot has been deployed in our lab and Amrita Institute of Medical Sciences, Kochi to sanitize the patient's rooms and bathrooms.

Novel research in the field of bioelectronic medicine requires systems that pair high-performance neurostimulation and bio-signal acquisition hardware with advanced software signal processing and control algorithms. Although mice are the most commonly used animal in medical research, the size, weight, and power requirements of such systems either preclude their use or impose significant constraints on experimental design. Here, we describe a fully-implantable neuromodulation system suitable for use in mice, measuring 2.2 cm3 and weighing 2.8 g. A bidirectional wireless interface allows simultaneous readout of multiple physiological signals and complete control over stimulation parameters, and a wirelessly rechargeable battery provides a lifetime of up to 5 days on a single charge. The device was successfully implanted (N=12) and a functional neural interface (capable of inducing acute bradycardia) is demonstrated with functional lifetimes exceeding to three weeks. The design utilizes only commercially-available components and 3D-printed packaging, with the goal of accelerating discovery and translation of future bioelectronic therapeutics.

In this paper, we focus on ensuring encrypted vehicular communication using wireless controller area network performance at high node densities, by means of Dedicated Short-Range Communication (DSRC) algorithms. We analyses the effect of the vehicular communication parameters, message-rate, data-rate, transmission power and carrier sensing threshold, on the application performance. After a state-of-the-art analysis, we propose a data-rate DSRC algorithm. Simulation studies show that DSRC performs better than other decentralized vehicular communication algorithms for a wide range of application requirements and densities. Vehicular communication plays one of the most important roles for future autonomous vehicle. We have systematically investigated the impact of vehicular communication using the MATLAB© application platform and achieved an accuracy of 93.74% after encrypting all the communications between the vehicles and securing them by applying the encryption on V2V communication in comparison with the existing system of Sensor Networks which stands at 92.97%. The transmission time for the encryption is 165 seconds while the rate of encryption is as low as 120 Mbps for the proposed awareness range of vehicles to vehicle using DSRC algorithm in Wireless-Controller Area Network for communication. Experimental results show that our proposed method performs 3% better than the recently developed algorithms.

Mobile Ad hoc Networks are decentralized networks in which participating nodes are mobile, small form-factor, equipped with the wireless interface, and have forwarding capabilities. These self-organized networks extend limited wireless range by the provision of multi-hop arrangements on the fly without any central administrator. In order to facilitate communication in a dynamic multi-hop wireless environment, routing protocols are essential to discover routes between nodes that are arbitrarily located and can move dynamically. Routing protocols are intended to discover the correct and efficient route in a timely manner so that information could be delivered to the desired destination node. Routing protocols are the backbone of the Mobile Ad hoc Networks and are challenging to design. Several works have been proposed on routing, and systematic representation of these proposals is desirable. In this paper, we provide a survey of the wide range of routing proposals in the last twenty years for the mobile ad hoc network. We device many categories and classification criteria untouched in most of the surveys. This survey paper gives a key overview of the protocols, also classifies and arranges the routing protocols for logical illustration. Protocol classification in the paper assists to systematically access a large set of protocols and highlights the research trends in the domain.

The optimal path problem can be considered as a type of discrete optimization, which enables reliable and QoS-aware data dissemination in Vehicular Ad Hoc Networks (VANETs). The optimal path is of great importance in vehicular communication due to frequently disconnected network, dynamic topology, and limited bandwidth of wireless interface. In this paper, multi-valued Discrete Particle Swarm Optimization (DPSO), including encoding and decoding phase, is used to optimize the process of identification of an optimal path for efficient data dissemination in VANETs. The proposed algorithm includes link stability calculated by Euclidean distance in the polar coordinate system and the probability of occurrence of obstacles as objective. Extensive simulations are utilized to analyze the effectiveness of the proposed technique on the metrics such as packet delivery ratio, average throughput, and routing overhead. The results obtained demonstrate that the proposed algorithm is better than the other related schemes in the existing literature.

Wireless technology is one of the most common technologies used in our day to day life. As wireless technology is very much easier to implement rather than wired, day by day its application is increasing. Through the continuous development of wireless communication technology it is now highly used in wireless equipment controlling. That is we can control our electronics and electrical equipments from a certain distant part. In this paper a multipurpose radio controlled car is designed with nRF24L01 wireless transceiver module, Arduino Uno R3 and DC motors to monitor risky areas. The RC vehicle is controlled by a distant controller or transmitter unit to move the vehicle to the risky location for monitoring.

With the emergence of connected and autonomous vehicles, sensors are increasingly deployed within cars to support new functionalities. Traffic generated by these sensors congest traditional intra-car networks, such as CAN buses. Furthermore, the large amount of wires needed to connect sensors makes it harder to design cars in a modular way. To alleviate these limitations, we propose, simulate, and implement a hybrid wired/wireless architecture, in which each node is connected to either a wired interface or a wireless interface or both. Specifically, we propose a new protocol, called Hybrid-Backpressure Collection Protocol (Hybrid-BCP) , to efficiently collect data from sensors in intra-car networks. Hybrid-BCP is backward-compatible with the CAN bus technology, and builds on the BCP protocol, designed for wireless sensor networks. We theoretically prove that an idealized version of Hybrid-BCP achieves optimal throughput. Our testbed implementation, based on CAN and ZigBee transceivers, demonstrates the load balancing and routing functionalities of Hybrid-BCP and its resilience to DoS attacks and wireless jamming attacks. We further provide simulation results, obtained with the ns-3 simulator and based on real intra-car RSSI traces, that compare between the performance of Hybrid-BCP and a tree-based data collection protocol. Notably, the simulations show that Hybrid-BCP outperforms the tree-based protocol on throughput by 12 percent. The results also show that Hybrid-BCP maintains high packet delivery rate and low packet delay for safety-critical sensors that are directly connected to the sink through wire.

Designers of fifth-generation (5G) wireless networks are focusing on enabling highly reliable low-latency communications that support a high data rate and allow massive connectivity. Nonorthogonal multiple access (NOMA), an essential enabling technology tailored to accommodate a wide range of communication requirements, shows potential as a tool for helping 5G networks to fulfill these promised capabilities. By coordinating connections for massive numbers of devices within the same resource block on power domain, frequency domain, or code domain, NOMA is superior to conventional orthogonal multiple access in terms of network connectivity, system throughputs, and other characteristics. Sparse code multiple access (SCMA) is a kind of multicarrier code-domain NOMA and has been studied extensively. The challenge in designing a high-quality SCMA system is crafting feasible encoding and decoding schemes to meet the desired requirements. In this article, we describe recent progress in designing multidimensional codebooks, a practical low-complexity decoder, and grant-free multiple access for SCMA systems. Our particular focus is on showing how the designs of the multidimensional constellation and factor graphs (FGs) have formed the foundation of SCMA codebooks. In addition, we review various lowcomplexity SCMA decoders with a special emphasis on sphere decoding. Also, we introduce SCMA grant-free transmission based on the framework of belief propagation (BP) and discuss the problem of collision resolution.

Purpose. Development of a laboratory stand with a wireless interface for the study and research of automatic control systems for DC electric drives. Methodology. Physical experiment on the developed laboratory bench, computer modelling, calculation and analytical methods. Findings. The study considered and analyzed the advantages and disadvantages of existing developments of laboratory stands with virtual and remote components, the possibility of organizing a wireless interface, taking into account cost-effectiveness, mobility, reliability and simplicity, as well as the possibility of using as a training stand. The connection of the stand by means of USB and Wi-Fi is developed. The STM32F103C8T6 microcontroller is used for the power switch and the automatic control system. The interface part consists of a NodeMCU board, a MicroSD card module, an interface control unit, a 16x2 LCD and an I2C converter. The UART-USB interface is used for information transfer and programming of the stand. The possibility of current remote transmission of information about the modes and parameters of the engine to a computer with a browser output by installing the Wi-Fi module ESP8266MOD. A closed system of automatic DC motor control with PID current regulators and EMF has been developed. Experiments were performed with a pulse and smooth increase in motor speed and variation of the components of the PID controllers using the control panel of the laboratory stand. All graphs of the results of the experiment were obtained on a web page with a fixed IP address in the browser via Wi-Fi. Originality. The structure of the remote monitoring and control system based on hardware and software combination of telecommunication and measuring systems is proposed and developed, which differs from the existing ones by the presence of current wireless transmission of information, which allows to remotely receive research data of automatic DC motor control systems. Practical value. The developed laboratory stand with the wireless interface allows to receive and store experimental data on parameters of the investigated engine in real time remotely., Цель работы. Разработка лабораторного стенда с беспроводным интерфейсом для изучения и исследования систем автоматического управления электроприводами постоянного тока. Методы исследования. Физический эксперимент на разработанном лабораторном стенде, компьютерное моделирование, расчетно-аналитический методы. Полученные результаты. В ходе исследования были рассмотрены и проанализированы преимущества и недостатки существующих разработок лабораторных стендов с виртуальной и дистанционной составляющей, возможностью организации беспроводного интерфейса, с учетом экономичности, мобильности, надежности и простоты исполнения, а также возможности использования в качестве учебного стенда. Разработано подключение стенда с помощью USB и Wi-Fi. Для силового коммутатора и системы автоматического управления использован микроконтроллер STM32F103C8T6. Интерфейсная часть состоит из платы NodeMCU, модуля MicroSD карты, блока управления интерфейсом, LCD 16x2 и I2C преобразователя. Для передачи информации и программирования стенда применен интерфейс UART - USB. Предусмотрена возможность текущей дистанционной передачи информации о режимах и параметры работы двигателя к компьютеру с выводом на браузер путем установки модуля Wi-Fi ESP8266MOD. Разработана замкнутая система автоматического управления двигателем постоянного тока с ПИД-регуляторами тока и ЭДС. Были проведены эксперименты с импульсным и плавным увеличением скорости двигателя и варьированием составляющих ПИД-регуляторов с помощью пульта управления. Все графики результатов эксперимента были получены на веб-странице с фиксированным IP-адресом в браузере через Wi-Fi. Научная новизна. Предложена и разработана структура системы дистанционного мониторинга и управления на основе аппаратно-программного совмещения телекоммуникационной и измерительной систем, которая отличается от существующих наличием текущей беспроводной передачи информации, позволяет дистанционно получать данные исследований систем автоматического управления двигателем постоянного тока. Практическая ценность. Разработанный лабораторный стенд с беспроводным интерфейсом позволяет дистанционно получать и хранить экспериментальные данные о параметрах исследуемого двигателя в режиме реального времени., Мета роботи. Розробка лабораторного стенду з бездротовим інтерфейсом для вивчення та дослідження систем автоматичного керування електроприводами постійного струму. Методи дослідження. Фізичний експеримент на розробленому лабораторному стенді, комп’ютерне моделювання, розрахунково-аналітичний. Отримані результати. В ході дослідження було розглянуто та проаналізовано переваги та недоліки існуючих розробок лабораторних стендів з віртуальною та дистанційною складовою, можливістю організації бездротового інтерфейсу, з урахуванням економічності, мобільності, надійності і простоти виконання, а також можливості використання як навчального стенду. Розроблено підключення стенду за допомогою USB та Wi-Fi. Для силового комутатора та системи автоматичного керування використано мікроконтролер STM32F103C8T6. Інтерфейсна частина складається з плати NodeMCU, модуля MicroSD карти, блоку керування інтерфейсом, LCD 16x2 з I2C розширювачем. Передбачено можливість поточної дистанційної передачі інформації про режими та параметри роботи двигуна до комп’ютера з виводом на браузер через модуль Wi-Fi ESP8266MOD. Розроблено замкнену систему автоматичного керування двигуном постійного струму з ПІД-регуляторами струму та ЕРС. Було проведено експерименти з імпульсним та плавним збільшенням швидкості двигуна та варіюванням складових ПІД-регуляторів за допомогою пульта керування. Всі графіки результатів експерименту були отримані на веб-сторінці з фіксованою IP-адресою в браузері через Wi-Fi. Наукова новизна. Запропоновано та розроблено структуру системи дистанційного моніторингу та керування на основі апаратно-програмного суміщення телекомунікаційної та вимірювальної систем, яка відрізняється від існуючих наявністю поточної бездротової передачі інформації, що дозволяє дистанційно отримувати дані досліджень систем автоматичного керування двигуном постійного струму. Практична цінність. Розроблений лабораторний стенд з бездротовим інтерфейсом дозволяє дистанційно отримувати і зберігати експериментальні дані про параметри досліджуваного двигуна у режимі реального часу.

The interest in the Internet of Things (IoT) is increasing both as for research and market perspectives. Worldwide, we are witnessing the deployment of several IoT networks for different applications, spanning from home automation to smart cities. The majority of these IoT deployments were quickly set up with the aim of providing connectivity without deeply engineering the infrastructure to optimize the network efficiency and scalability. The interest is now moving towards the analysis of the behavior of such systems in order to characterize and improve their functionality. In these IoT systems, many data related to device and human interactions are stored in databases, as well as IoT information related to the network level (wireless or wired) is gathered by the network operators. In this paper, we provide a systematic approach to process network data gathered from a wide area IoT wireless platform based on LoRaWAN (Long Range Wide Area Network). Our study can be used for profiling IoT devices, in order to group them according to their characteristics, as well as detecting network anomalies. Specifically, we use the k-means algorithm to group LoRaWAN packets according to their radio and network behavior. We tested our approach on a real LoRaWAN network where the entire captured traffic is stored in a proprietary database. Quite important is the fact that LoRaWAN captures, via the wireless interface, packets of multiple operators. Indeed our analysis was performed on 997, 183 packets with 2169 devices involved and only a subset of them were known by the considered operator, meaning that an operator cannot control the whole behavior of the system but on the contrary has to observe it. We were able to analyze clusters’ contents, revealing results both in line with the current network behavior and alerts on malfunctioning devices, remarking the reliability of the proposed approach.

It is estimated that about 17,700 (2015) people die every year in India due to fire and lack of its prevention on time and facilities (Litta et al., Flexible platform with wireless interface for DC-motor remote control, 2018, pp. 509–514 [1]). In many cases, the firefighter loses their lives during the extinguishing by excessive heat. Therefore, a technological solution can help to prevent life from such kind risky operation. Here, to lessen these accidents, we have modeled a robot which is capable to fight the fire using water during its extinguishing by Bluetooth-based automatic process. The extensive use of improved Bluetooth technology and advancement in the IR sensors help us to design a model-based solution for this particular problem.

A handheld device (such as a smartphone/wearable) can be used for tracking and delivering navigation within a building using a wireless interface (such as WiFi or Bluetooth Low Energy), in situations when a traditional navigation system (such as a global positioning system) is unable to function effectively. In this paper, we present an indoor navigation system based on a combination of wall-mounted wireless sensors, a mobile health application (mHealth app), and WiFi/Bluetooth beacons. Such a system can be used to track and trace people with neurological disorders, such as Alzheimer’s disease (AD) patients, throughout the hospital complex. The Contact tracing is accomplished by using Bluetooth low-energy beacons to detect and monitor the possibilities of those who have been exposed to communicable diseases such as COVID-19. The communication flow between the mHealth app and the cloud-based framework is explained elaborately in the paper. The system provides a real-time remote monitoring system for primary medical care in cases where relatives of Alzheimer’s patients and doctors are having complications that may demand medical care or hospitalization. The proposed indoor navigation system has been found to be useful in assisting patients with Alzheimer’s disease (AD) while in the hospital building.

Network-on-Chip (NoC) is popularly used for interconnecting multiple cores in modern System-on-Chips (SoCs). The design intricacy of NoC is growing with the increasing complexity of SoCs. This results in multiple bugs being present on the interconnect module even after the pre-silicon verification stage. Hence, efficient post-silicon debug mechanisms should be employed to detect the skipped bugs and provide an error-free NoC. This chapter highlights different steps involved in the NoC post-silicon validation and debug process such as packet trace collection, trace data transfer, and fault analysis. An overview of the debug infrastructures like monitoring unit, trace buffer, trace bus, etc. is presented. This chapter also demonstrates a wireless enabled NoC debug framework that enhances the observability of the network, and speeds up the whole debugging process. Moreover, reuse of trace buffer as NoC virtual channels is illustrated for enhancing the network performance.

Electrical Impedance Tomography (EIT) is a non-invasive medical imaging technique, in which the bio-impedance of a part of the body is inferred from surface electrode measurements and used to form a tomographic image of that part. EIT is particularly useful for monitoring lung function because the resistivity of the lung tissue is higher than most other soft tissues in the thorax. Lung tissue resistivity also decreases several folds between inhalation and exhalation, which explains why monitoring ventilation is currently the most promising clinical application of EIT. EIT plays a crucial role in monitoring patients aided by mechanical ventilation, as the usage of mechanical ventilation frequently results in ventilator-associated lung injury (VALI). To enable portability and continuous remote monitoring of patients, it is desirable to incorporate wireless transmission capability to the EIT device. The main objective of this research is to design and establish a wireless interface for the transmission of bio-impedance data from the human body, to obtain real-time tomographic imaging.

The context of Industry 4.0 emphasizes on networking of manufacturing stations to a remote server for process planning and visualization. Especially for electronics production which is sensitive to process variations, networking of the manufacturing stations facilitates the monitoring of manufacturing stations remotely. In contrast with manual look up of the machines, the aforementioned approach allows prompt notification in real-time to manufacturer for immediate resolution and as a result, breakdown time of the production can be minimized. Therefore, this paper presents a wireless interface system for electronics microfabrication stations. Each microfabrication stations are interfaced with a WiFi module for wireless data transmission to a remote server established on Raspberry Pi. The experimental setup and testing of the developed system is presented in this paper for public interest.

Industrial controller systems are crucially essential to the cutting edge power systems industries. Electric services are expected to determine the best media tool to be used for any distribution. The communication systems contribute towards a physical intermediary layer for transferring, controlling and acquirement of data within the system from distant locations. This paper discusses the Supervisory Control and Data Acquisition (SCADA) systems and proposes a similar system that is an IoT based industrial wireless controller. The proposed system can control multiple devices through the internet without the need to be physically near the devices. Because it uses simple and cheap devices, the system is low cost and easy to install. Additionally, the system is modular because extra microcontrollers can be added to the system to control more devices should the need arise.

An artificial intelligence wireless stimulating system-on-chip (AIWSSoC) is proposed in this study. The AIWSSoC integrates two EEG monitoring channels, wireless interface and charging, a UART interface, an epilepsy detection algorithm, a power management circuit, an electrical stimulation circuit, and an optogenetic stimulation controller into a chip. Moreover, the AIWSSoC functions as a seizure suppressor with an off-chip device. Animal experimental result verifies the function of recording and different types of electrical stimulations.

This paper provides a mobile apparatus for medical application which comprises a medical trolley, automatic guidance, a wireless controller, human follower using ultrasonic sensors, an obstacle avoiding detection device, an IP camera, a smartphone touch screen controller, an integrated power supply, and a processor. The trolley with stainless steel shelves is ideal for use in clinical environments and operation theatres. The wireless remote drives the trolley to move forward and backward. An IP camera is attached to the trolley to provide visual guidance controlled using a smartphone. The system uses ultrasonic sensors for human follower. Arduino Development Board is used as the processor for the automated mobile trolley system. The implementation of the system can save a large amount of space. The workload of medical workers will be greatly relieved and the working efficiency can be improved.

In this work we demonstrate the NITOS Wireless Sensor Network testbed that allows remote and reproducible experimentation at city-scale, employing long-range wireless protocols. Specifically, we deploy 10 custom-made LoRa-enabled nodes in the city of Volos, Greece, coupled with an embedded device utilized as a means to provide remote access and configuration as well as for monitoring the experiments upon execution. Moreover, the testbed offers power consumption monitoring capabilities being able to capture the power draw of the entire sensor node, while also of individual modules such as the attached wireless interface, to characterize the energy-efficiency of new protocols.

The gastro-intestinal (GI) tract is a very important part of the human digestive system but remains largely inaccessible for unobtrusive monitoring. Ingestible electronic devices are a very interesting concept to address this need. This paper discusses the current state of ingestible electronic devices and explores the potential they hold to provide unprecedented insight by measuring several aspects of the complex bio-chemical processes that happen in the GI tract in real-time. This will require novel sensor technology capable of measuring relevant markers with adequate specificity and accuracy. In order to be able to scale this functionality down to a form factor of an easily digestible pill, ultra-low-power wireless interface electronics are needed. This poses certain challenges and innovation opportunities related to sensing, wireless communication and powering to enable the next generation of ingestible electronic devices. [2020-0164]

Air pollution is a major environmental problem and causes serious damage to human health. Considering the COVID-19 pandemic scenario, the importance of monitoring and controlling pollution emissions becomes more relevant and fundamental for combating the disease. Seeking to contribute with technological tools, this work presents a proposal for a system based on IoT using low sensors to monitor the most novice pollutants to health, according to the recommendations of the World Health Organization. The proposal presents the development in the hardware layer of a device able to measure the concentrations of the following pollutants: Particulate Material (PM 2.5 and PM 10 ), Ozone, Carbon Monoxide, Nitrogen Dioxide and Ammonia by means of three sensors, respectively, PMSA003, MICS-6814 and MQ-131. The device is be equipped with the ESP-WROOM-32 microcontroller that has a Wi-Fi and Bluetooth wireless interface that will allow data to be sent to a server in the cloud. It is important to note that what differentiates from the proposal from others is the implementation of periodic notifications and the sending of alerts for cases in which a given pollutant has reached the maximum acceptable concentration.

Intelligent Transportation Systems (ITS) are expected to play a vital role in increasing road safety and road efficiency in the near future. The primary feature of ITS applications is to provide road safety, which is based on IEEE-802.11p technology, by transmitting safety messages to the vehicles in the surrounding. The channel congestion is a significant challenge for the IEEE802.11p, ITS is operating on. Congestion increases the data loss and degrades the ITS performance resulting from compromising passengers safety. In this paper, we analyze the benefits of exploiting vehicle's embedded sensors to enhance car perception and hence improve the efficiency of cooperative communications. To this purpose, we implemented the collaborative environment perception approach for vehicular safety applications proposed by [1] and analyze its performance and behavior in congested urban traffic. In this proposal, so-called ECAM (Extended Cooperative Awareness Message), vehicles use a different type of sensors (cameras, radars, lidars etc.) to collect the status information of the surrounding vehicles in their detection range and share this information through a collaborative beaconing scheme to reduce congestion on the communication channel. This scheme implements a dual step mechanism to function. The first phase implements the collaborative perception mechanism by adding the locally collected information in the safety message and sharing this up to date data to intensify the awareness among the vehicles in its communication surrounding. In the second phase, the recipient vehicles verify the accuracy of the information received from the collective perception enabled vehicles by leveraging the position by adding an error threshold. Performance evaluation conducted through extensive simulations shows the benefits of exploiting increased perception to enhance awareness among cars while reducing the contention on the wireless interface.

IoT (Internet of Things)-based remote monitoring and controlling applications are increasing in dimensions and domains day by day. Sensor-based remote monitoring using a Wireless Sensor Network (WSN) becomes challenging for applications when both temporal and spatial data from widely spread sources are acquired in real time. In applications such as environmental, agricultural, and water quality monitoring, the data sources are geographically distributed, and have little or no cellular connectivity. These applications require long-distance wireless or satellite connections for IoT connectivity. Present WSNs are better suited for densely populated applications and require a large number of sensor nodes and base stations for wider coverage but at the cost of added complexity in routing and network organization. As a result, real time data acquisition using an IoT connected WSN is a challenge in terms of coverage, network lifetime, and wireless connectivity. This paper proposes a lightweight, dynamic, and auto-reconfigurable communication protocol (LDAP) for Wide-Area Remote Monitoring (WARM) applications. It has a mobile data sink for wider WSN coverage, and auto-reconfiguration capability to cope with the dynamic network topology required for device mobility. The WSN coverage and lifetime are further improved by using a Long-Range (LoRa) wireless interface. We evaluated the performance of the proposed LDAP in the field in terms of the data delivery rate, Received Signal Strength (RSS), and Signal to Noise Ratio (SNR). All experiments were conducted in a field trial for a water quality monitoring application as a case study. We have used both static and mobile data sinks with static sensor nodes in an IoT-connected environment. The experimental results show a significant reduction (up to 80%) of the number of data sinks while using the proposed LDAP. We also evaluated the energy consumption to determine the lifetime of the WSN using the LDAP algorithm.

Unobtrusive and continuous monitoring of vital signs is becoming more and more important both for patient monitoring in the home environment and for sports activity tracking. Even though many gadgets and clinical systems exist, the need for simple, low-cost and easily applicable solutions still remains, especially in view of a more widespread use within everyone&rsquo, s reach. The paper presents a fully wearable and wireless sensorized belt, suitable to simultaneously acquire respiratory and cardiac signals employing a single acquisition channel. The adopted method relies on a 50-kHz current injected in the subject thorax through a couple of textile electrodes and on envelope detection of the trans-thoracic voltage acquired from a couple of different embedded electrodes. The resulting signal contains both the baseband electrocardiogram (ECG) signal and the trans-thoracic impedance signal, which encodes respiratory acts. The two signals can be easily separated through suitable filtering and the cardio&ndash, respiratory rates extracted. The proposed solution yields performances comparable to those of a spirometer and a two-lead ECG. The whole system, with a realization cost below 100 &euro, a wireless interface, and several hours (or even days) of autonomy, is a suitable candidate for everyday use, especially if complemented by motion artifact removal techniques, currently under implementation.

This paper is mainly focused on producing a completely modernized IA distribution controlling system including PLC program and HMI package overcoming all the disadvantages with its older version using relay logic. As a further extension Industry 4.0 is incorporated by using LabVIEW as HMI and wireless interface of sensors and mimicking the IAD plant in Arduino and web-publishing the same for remote access.

International audience; Flexible crack-based strain sensors showing a maximum gauge factor of 30,000 at 0.2% strain level are elaborated by means of Atomic Layer Deposition and e-beam evaporation. It is shown that the mechanosensitivity can be drastically boosted by encapsulating the cracks with a photoresist layer. A non-invasive portable device integrating this ultrasensitive flexible transducer is then developed to monitor the cardiac activity at rest. The presented prototype integrates a Bluetooth Low Energy wireless interface for realtime communication with an Android mobile device.

This paper presents the first wireless multiplexed fluorescence-based bio-molecular sensing system in a pill form for GI-track health monitoring application. This application is geared towards quasi-real time analysis of microbiome distribution through nucleic acid detection. A silicon chip integrates both the sensor and the wireless system, including a 124 μW ULP wireless receiver with −59 dBm sensitivity, a dual mode FSK/OOK transmitter, and a fluorescent sensor array with 1.6 attomoles and 100 pM of target DNA detection limit per pixel. The complete package includes a CMOS fluorescent sensor chip with integrated filter, a prototyped UV LED and optical waveguide, functionalized bioslip, off-chip power management and Tx/Rx antenna that fits in a standard FDA approved capsule size 000.

Water is the most precious natural resource and it is most essential for all kinds of living organisms. So, our primary duty is to prevent the excessive wastage of water. In this project, a system to measure the level of water is made by using an ultrasonic sensor. When the water level reaches the maximum or minimum level (according to the tank size) the sensor transmits a signal to the microcontroller through the wireless interface and after receiving the signal the microcontroller displays the water level by the inbuilt LCD and there is a command by the speaker to turn on or off the motor. By using this system, it helps to reduce the human effort to turn ON or OFF water pump maintaining a particular schedule. It helps unnecessary wastages of water. It reduces the power consumption during the overtime run of the motor which is a reasonable choice in today's Indian economy. This system is automatic and smart.