In recent times, Internet of Things (IoT) has become a hot research topic and it aims at interlinking several sensor-enabled devices mainly for data gathering and tracking applications. Wireless ...Sensor Network (WSN) is an important component in IoT paradigm since its inception and has become the most preferred platform to deploy several smart city application areas like home automation, smart buildings, intelligent transportation, disaster management, and other such IoT-based applications. Clustering methods are widely-employed energy efficient techniques with a primary purpose i.e., to balance the energy among sensor nodes. Clustering and routing processes are considered as Non-Polynomial (NP) hard problems whereas bio-inspired techniques have been employed for a known time to resolve such problems. The current research paper designs an Energy Efficient Two-Tier Clustering with Multi-hop Routing Protocol (EETTC-MRP) for IoT networks. The presented EETTC-MRP technique operates on different stages namely, tentative Cluster Head (CH) selection, final CH selection, and routing. In first stage of the proposed EETTC-MRP technique, a type II fuzzy logic-based tentative CH (T2FL-TCH) selection is used. Subsequently, Quantum Group Teaching Optimization Algorithm-based Final CH selection (QGTOA-FCH) technique is deployed to derive an optimum group of CHs in the network. Besides, Political Optimizer based Multihop Routing (PO-MHR) technique is also employed to derive an optimal selection of routes between CHs in the network. In order to validate the efficacy of EETTC-MRP method, a series of experiments was conducted and the outcomes were examined under distinct measures. The experimental analysis infers that the proposed EETTC-MRP technique is superior to other methods under different measures.
A game based virtual campus tour Razia Sulthana, A; Arokiaraj Jovith, A; Saveetha, D ...
Journal of physics. Conference series,
04/2018, Letnik:
1000, Številka:
1
Journal Article
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The aim of the application is to create a virtual reality game, whose purpose is to showcase the facilities of SRM University, while doing so in an entertaining manner. The virtual prototype of the ...institution is deployed in a game engine which eases the students to look over the infrastructure, thereby reducing the resources utilization. Time and money are the resources in concern today. The virtual campus application assists the end user even from a remote location. The virtual world simulates the exact location and hence the effect is created. Thus, it virtually transports the user to the university, with the help of a VR Headset. This is a dynamic application wherein the user can move in any direction. The VR headset provides an interface to get gyro input and this is used to start and stop the movement. Virtual Campus is size efficient and occupies minimal space. It is scalable against mobile gadgets. This gaming application helps the end user to explore the campus, while having fun too. It is a user friendly application that supports users worldwide.
Presently, a green Internet of Things (IoT) based energy aware network plays a significant part in the sensing technology. The development of IoT has a major impact on several application areas such ...as healthcare, smart city, transportation, etc. The exponential rise in the sensor nodes might result in enhanced energy dissipation. So, the minimization of environmental impact in green media networks is a challenging issue for both researchers and business people. Energy efficiency and security remain crucial in the design of IoT applications. This paper presents a new green energy-efficient routing with DL based anomaly detection (GEER-DLAD) technique for IoT applications. The presented model enables IoT devices to utilize energy effectively in such a way as to increase the network span. The GEER-DLAD technique performs error lossy compression (ELC) technique to lessen the quantity of data communication over the network. In addition, the moth flame swarm optimization (MSO) algorithm is applied for the optimal selection of routes in the network. Besides, DLAD process takes place via the recurrent neural network-long short term memory (RNN-LSTM) model to detect anomalies in the IoT communication networks. A detailed experimental validation process is carried out and the results ensured the betterment of the GEER-DLAD model in terms of energy efficiency and detection performance.
Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents ...an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Wireless Sensor Networks (WSN) is in large use in today’s world against the challenges encountered in the Sensor world. Energy consumption, routing, interference mitigation are a matter of concern in ...WSN. Perhaps, overruling interference mitigation would solve a number of interconnected problems in WSN. The proposed work is narrowed down to minimize interference in distributed homogenous WSN, ensuring that all the nodes in the network operate with the same transmission power. In this paper, an optimal shortest distance algorithm, Dynamic-Optimal Shortest Path Algorithm (DOSPA) is proposed to identify the shortest path in communication between point to point nodes. As the data traverses a number of intermediary nodes, a privileged network topology has to be built to ensure proper transmission of data. An ideal network topology is hence built dynamically for data transmission. However, a collision between data packets in interconnecting nodes is likely to occur. Furthermore, to minimize collision a non-persistent round-robin CSMA/CD algorithm is proposed. We study the network throughput, packet delay, corruption ratio by increasing the number of nodes and hence also analyzing the system in saturation state. It’s found that Packet Corruption Ratio (PCR) with CSMA+DOSPA is minimized compared to CSMA. Thus, interference reduction in distributed homogenous nodes is substantially minimized.
Cellular proliferation in the lung tissues is a hallmark of lung cancer. Lung cancer is particularly dangerous since the lungs are responsible for both breathing in oxygen and exhaling carbon ...dioxide-two of the body's most vital functions. The application of deep-learning (DL) for the identification of lymph node involvement on histopathology slides has gained a lot of attention due to the potential impact it could have on patient diagnosis and therapy. Recognition accuracy, precision, sensitivity, F-Score, specificity, etc., are all significantly lower with the current approach. Convolution-Neural-Network (CNN), CNN Gradient-Descent (CNN GD), VGG-16, VGG-19, and Resnet-50 are just few of the deep learning algorithms that exhibit improved performance in the metrics with the proposed methodology. CT scan pictures and histopathology images are used to evaluate the suggested method. When histopathological tissues are analyzed, the results demonstrate that detection accuracy improves.
Fisherman Navigation and Safety System Krishnan, M.B. Mukesh; Saveetha, D.; Jovith, A.Arokiaraj ...
International journal of innovative technology and exploring engineering,
10/2019, Letnik:
8, Številka:
12
Journal Article
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The fisherman’s crossing the borders and identification of locations in the sea is becoming a difficult task with existing equipment’s provide to the fisherman’s as a result they cross the borders. ...In our day-to-day life we hear about many Tamil Fishermen being caughtand put under Sri Lankan Naval custody. The sea border between thecountries is not easily identifiable, which is the main reason for this offence. Moreover, in cases of imminent natural disasters, failure or delayin notifying concerned personnel to evacuate results in loss of life on alarge scale. In this paper we have proposed a method which protects thefishermen by logging their entries and exits in the harbour using embeddedsystem, notifying the country’s sea border to them by using Global Positioning System (GPS), GeoFencing and Mobile Systems. We use GPSas a method to track the current location of the fishermen. The GPS’current latitude and longitude coordinates are sent to the database wherethe administrator utilizes it for continuous tracking and monitoring of theuser, if in distress using their credentials and last known location, currentlocation predictions can be made. Another benefit being the logging procedures help official authoritative agencies to identify fishermen and their activities for their own safety and security.
A key component of precision agriculture is crop recommendation, which strives to maximize the harvest by taking into account ecological and soil variables. Utilizing light Gradient Boosting Machine ...(LGBM) algorithm intrinsic simplicity and clarity, we put forward an ensemble-based approach for crop recommendation in this work. The algorithm leverages a record of past crop yield and soil type to account for a number of parameters, including pH, soil nutrient levels, and weather patterns. According to our insights, this LGBM algorithm is a useful tool that generates precise and coherent crop suggestions, which supports productive and organic farming techniques. Using a random forest approach, this study attempts to anticipate fertilizer and assist farmers in making educated decisions on auxiliary fertilizer use. For a given set of input parameters, the model predicts the ideal type and quantity of fertilizer needed by using a random forest method. The random forest approach is precise and helpful in recommending fertilizer with precision, which supports resource-efficient and sustainable farming practices, as evidenced by experiments.
The Industrial Internet of Things (IIoT) has brought a new era of improved equipment monitoring and operational data management in manufacturing and other industrial settings. This research presents ...the use cases and benefits of IIoT sensor networks for gathering actionable insights and operational data from industrial machinery. Reliable IIoT sensor networks are built, including the design, deployment, data collecting, and cloud computing techniques. The achieved using constant, up-to-the-minute monitoring; reduced data collecting; and enhanced productivity. Data security, network stability, and scalability of the problems that develop during the deployment of IIoT sensor networks are covered in this paper. These networks might benefit from cloud computing to better manage and analyze the massive amounts of data the produce. The broader impacts of setting up IIoT sensor networks include savings in money and time and the ability to make more informed decisions based on data. It highlights the evolution of conventional industrial landscapes into linked ecosystems that may provide insightful decision-making data. The data for users to use sensor networks to monitor equipment and improve productivity. Reducing equipment downtime by 30% and increasing operational efficiency by 20% are both made potential by combining Industrial IoT sensor networks with cloud analytics. With an 80% success rate, maintenance techniques save a ton of money and make things more efficient.
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