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Wireless Sensor Network (WSNs) plays a vital role in smart grid (SG) environment. Due to the fault tolerance characteristics, cost reduction and large scale convergence. SG introduce many unique challenges caused by system and functional devices. To solve this problem, a WSN based SG network is used for identifying faults. During the process of data transmission, faulty nodes are occurred in the transmission line. Due to the nodes failures, calibration, network failures, low battery, dried sensors, environmental changes and software failures etc., which leads to the interruption in data delivery and spoil the entire WSN based SG network. In order to tackle these problems, the new WSN model is designed to detect the faults in the transmission line based on the SG environment. In this paper, Adaptive Zigbee-Aquila communication protocol (AZACP) is used to find the optimal shortest path for transferring data. AZACP finds the shortest optimal path for transmitting the sensed data to base station with low cost and less time consumption. Fault detection is the process of automatically identifying the fault in the transmission line and isolate the faulty nodes to ensure the efficient data transmission in WSN. Here, Enhanced Recurrent Equilibrium Neural Network (ERENN) is introduced to identify the fault in data transmission. It recognize the strength of the signal to transmit the sensed data and checks the quality of the data in transmission line between the nodes. The proposed approach is implemented in MATLAB software and compared with existing approaches like Adaptive Error Control (AEC), Gallager Humble Spira (GHS), Genetic Algorithm-Ticket Based Routing (GA-TBR), Improved Grid based Routing and Charging (IGRC) and Emperor Penguin Optimized Self-healing Strategy (EPOSH). The proposed approach provides better performance in terms of evaluating performance metrics like throughput, delay, reliability, average residual energy, number of total transmission, network lifetime, efficiency and Bit Error Rate (BER).

Scaling technology and shrinking transistor size have enabled the integration of multicore modules on a single chip for high-performance computing. Wireless Network-On-Chip (WNOCs) has been demonstrated to be a viable choice for on-chip communication compared with wired communication, considering latency, energy, and data rate as performance metrics. Limitations in on-off keying (OOK) modulation schemes have been addressed using OFDM modulation methods. In this paper, a new method based on the compressed sensing integrated dual tree complex wavelet transform (CS-DTCWT) is presented for OFDM modulation and demodulation operating in the mm-wave band. The CS-DTCWT-based OFDM model is developed in MATLAB and evaluated for its performance in the mm-wave operating frequency band of 20 GHz to 60 GHz and for subcarriers of 128 to 1024. The BER performances of CS-DTCWT-based OFDM are demonstrated to be an improvement of 80% compared to FFT-based OFDM techniques. In addition, it can save 3.11% more energy than existing works. The proposed OFDM model is suitable for wireless NOC applications.

With technology scaling and to meet the desired design for low power and high-speed circuit, innovative design is being studied. The simulation study of vertical Quad gate oxide stacked junction-le...

Mobile sink based data collection has comparatively lower energy consumption compared to multi hop forwarding in wireless sensor networks. Energy efficiency is achieved by minimizing the hop count to sink in mobile sink based approaches. These approaches are of two types: Mobile sink collect stored data at rendezvous nodes or cluster heads forwarding data to mobile sink without storage by using its maximum transmission range. First approach provides higher energy gain at cost of delay. Second approach provides lower delay at cost of additional energy consumption. This work combines both the approaches with rendezvous node deciding to store or forward based on prediction of trajectory of multiple mobile sinks and packet latency deadlines.

Water is a very valuable and stimulating force for irrigation. The Optimum usage of water is an hourly requirement. Efficient irrigation helps to conserve water, increase plant yields, reduce fertilizer reliance, and improve the quality of crops. Various techniques are available to measure soil moisture content, both laboratory and field, including remote sensing, but the fastest and better one is with the use of soil moisture sensor electronic devices. The range of soil moisture sensors has its own benefits and drawbacks. The goal of this work is to design and develop a module for the measurement of soil moisture and temperature levels, as well as ambient temperature and humidity by using frequency concepts. The sensor is made of a corrosion resistant element and it is rugged, battery operated, low power and long range sensor using IoT. A “GND BLE Mobile Application (gSense100)” has been developed, which includes everything related to the BLE technology and soil moisture sensor, where the app uses BLE technology to transmit all sensor values to the consumer.

In this study, the Quad gate with gate oxide stack for 3 fins which is a vertically stacked device for the classical model and added the quantum mechanical effects to classical refers to the quantu...

The soil nutrients nitrogen, phosphorous and potassium (NPK) are primary and vital components for an agricultural land to be fertile. The excess or under usage of fertilizers will hamper the characteristics of the soil. The improper selection of manure would reduce the yield of the crop, resulting in loss of the yield. The proposed work aims at developing a sensor using the principle of optical transducer and hence determining NPK nutrients in the solution using Beer–Lamberts law. Also, under or over irrigation would lead to loss of the crop. The proposed method also aims at providing irrigation monitoring using a soil moisture sensor which determines water content in the soil using principle of conductivity. The system is developed as a three-tier application having sensors as data acquisition layer. The wireless communication is using Bluetooth as data link/data communication layer. Finally, Android mobile application is the presentation layer. The work aims at providing best-suited fertilizer along with optimal amount of fertilizer that gives high yield. In comparison with existing methods in same domain, the proposed work is economical and time efficient.

Navigating in unknown places can be challenging for people who are deprived of the benefit of sight. The focus of advancements in navigation systems is extended onto helping the visually impaired understand the structure of their surroundings whilst they are traveling. The main idea behind the proposed method is to eliminate the dependency of the visually impaired on unreliable sources in an unfamiliar locality. Most of the public buildings these days, such as college and office buildings are equipped with their own Wi-Fi network which is used by the proposed indoor navigation assistant to direct the user while navigating inside the building. Using the Received Signal Strength Indicator (RSSI) values that are taken from each access point, trilateration is performed for localization, and the speech output guides the person by informing about the current location and thus making it possible for the visually impaired to move inside a building without any human assistance.

The electrocardiogram (ECG or EKG) signal plays an essential role in the field of medical science and is used in the diagnosis of various cardiovascular diseases (CVD). If the recorded ECG signal has an irregularity in the heartbeat rhythm, it is known as arrhythmia. The diagnosis is done based on ECG morphology. Heartbeat can be subdivided into five categories such as normal, supraventricular ectopic, ventricular ectopic, fusion and unknown beats. In this paper, the authors present an easy and effective way for analysing and diagnosing the nature of the arrhythmia using 1D convolutional neural network (CNN). The ECG data set was obtained from PhysioNet’s MIT-BIH database. The PyTorch library was used in python in designing the CNN model which classifies the ECG test sample signal to a category. The diagnosed signal along with the patient details is sent to a cardio specialist for validation via mail and to the CVD forum android application where the case history can be maintained in the database and can be reviewed by any cardio specialist. The CNN model was trained using the data sets and achieved an average accuracy of 97.72%, and the classification achieved is presented in a confusion matrix.

Lip reading is the ability to understand what a person is communicating using just the video information. Due to the advent of Internet and computers, it is now possible to remove human intervention from lip reading. Such automation is only feasible because of a couple of developments in the field of computer vision: availability of a large-scale dataset for training and use of neural network models. The applications to this are numerous. From dictating messages to a device in a noisy environment to improving speech recognition in the current technologies, visual speech recognition has proved to be pivotal. In this paper, the lip-reading models are based on deep neural network architectures that capture temporal data which are created for the task of speech recognition.

OFDM is the most efficient methods for the transfer of high to low data rate in the wireless communication system. It has ‘N’ number of advantages namely immune to multi fading, lesser inter symbol interference and high spectral efficiency. Despite the hyp, OFDM also has the disadvantage of having a very high PAPR i.e. PAPR ratio. In the view of reducing PAPR, clipping and filtering system is commonly employed and the reduction of PAPR is observed by varying clipping levels and symbol size.

MANETs are emerging as the torrid research topic in the wireless communication domain. These MANETs are used in emergency cases like military, flood, earthquake, etc. to set-up a fast, easy and feasible network. Proactive is a table-driven protocol, consists of routing table information before setting up a connection. Reactive protocols setup path only when it is demanded by the network. In this paper, we have proposed a protocol that combines the advantages of both cluster-head gateway switch routing protocol (CGSR) and adhoc on-demand distance vector (AODV) to minimize the traffic congestion in ad-hoc wireless network. The results of performance metrics like routing overhead, end-end delay, and packet delivery ratio are enhanced and compared with other clustering protocols like CGSR, LEACH, and DUCS.

Internet of Things (IOT) aims at interfacing different gadgets to the internet web – encouraging human-machine and machine-machine connections offering superior security, console and effectiveness. The concept of IOT is utilized in this model, remote monitoring of energy meter which is intended to overcome the issues in existing Automatic Meter Reading (AMR) system. It spares tremendous human work. A controller integrated with electronic energy meter assist in distant correspondence from the developed android application. This application enables monitoring of bill generation at consumer premises without human intervention and also in visualizing live data consumption and sight energy expended points of interest on daily/monthly basis. In addition, it gives authority to power organizations to seize lenient customers who have extraordinary dues for remote disconnection of the power supply. So IOT based remote AMR framework is more viable methodology than tradition of billing framework. General Terms Central office

In Wireless Sensor Networks (WSNs), the reduction of energy consumption in the batteries of a sensor node is an important task. Sensor nodes of WSNs perform three significant functions such as data sensing, data transmitting and data relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for sensing and transmitting the data. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Network simulator 2 is used for experimentation purpose. This work also compares with the existing routing protocols like Energy-efficient Low Duty Cycle (ELDC), Threshold sensitive Energy Efficient sensor Network (TEEN) and Adaptive clustering protocol. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio.

Data links which flow in sequential manner for communication in global manner on chips or IC's have evolved and given birth to lot of investigations in recent times. As a result of this evolution lately it was proved that serial link communication gives major advantage over multi-bit or parallel communication with respect to reduce problems likeskew, jitter, area, cost, wiring problem and clock synchronization. The reason behind choosing of serial or sequential link over multi bit is to reduce or cut down routing congestion and complexity in the design issues. This will bring down major part of power consumption which occurs due to enhanced switching rate in the chips. This paper distinguishes a new bit regularization scheme in order to scale down data switching action with in the serial links with an assumption that statistical information of the data bits on the parallel data links is known is priori.

This paper explores the use of high-k material in place of SiO2 in MOSFET for 14nm technology, new device materials are required that can enhance the performance of MOSFET. The use of high-k material in MOSFET can triumph over the problem of power dissipation and leakage current. This paper explores the suitability of HfO2 as gate dielectric material at 14nm technology. The performance of the device was tested through simulation using sentaurus structure editor in TCAD. The device shows a good refinement on its result of subthreshold leakage current, Ioff, and drive current, Ion for HfO2 dielectric constants (k). The simulation results reveal that Ion / Ioff reduce by 62.94%, which proves that HfO2 is the best dielectric material and it can replace SiO2.

In communication field one of the recent emerging technology is the wireless technology. The wireless communication provides high data transmission for a growing idea of 4G and 5G communications. The high data rate transmission cannot be obtained by single carrier, so multicarrier modulation where we make use of subcarriers orthogonal to each other i.e, OFDM signal. The main drawback of this signal is high peak to average powers which causes distortion like in-band and out-band radiation. This survey paper presents different PAPR reduction techniques.

Wireless Sensor Networks, the existing techniques for sink deployment consider load balancing and multipath routing. But the fault detection and recovery of sinks are rarely considered. In this paper, we propose to develop a Fault detection and recovery mechanism for multiple sinks. The nodes are grouped into clusters based on the data generation rate and multiple sinks are deployed in the clusters in which the data generation rate is more. An energy efficient multi path tree is constructed towards the sink and the aggregated data from the sensors are transmitted to their nearest sinks through this multi path tree. The rate adjustment value and the inter arrival delay of each path is calculated and sent back as a feedback to the source to by the respective sinks. Then the path with the minimum feedback value is chosen as the best path for transmission. When a failure occurs in a sink, then it can be detected based on delay and remaining energy. Once the fault sink is detected, then the data is transferred to another sink or the sinks are deployed again. From our simulation results, we show that an efficient load balanced multi path routing for multiple sinks is obtained and the fault detection and recovery can be made effectively.