Published in 2026
Bhavana B R, Chaithra H E, Manasa B S
The effectiveness and the efficiency of the Wireless Sensor Networks (WSNs) entirely depend on the data accumulation method. Numerous data accumulation methods like multipath, tree, chain, hybrid and cluster topologies are available in the past for accumulating data in WSNs. The subsisting data accumulation methods in the past don’t provide an assured reliable network from the perspective of movement of delay, speed, and connection time. A Link-aware and Velocity Energy-efficient Cluster-Tree (LAVECT) topology for accumulation of data in WSNs with the avail of special nodes called data accumulation node (DAN) constructs a tree, which is an optimal path to the sink, which would in turn efficiently resolve the coverage distance, energy exploitation, mobility of sensor nodes, delay in packet distribution, traffic in the network, intensity of the tree constructed and connection time problems. The discovered LAVECT scheme constructs the Data Accumulation Tree (DAT) predicated on the cluster head location in the network. It additionally maintains the cluster for a considerable duration, thus incrementing the connection time. Simulation results show that LAVECT provides better performance from the perspective of energy utilization by the nodes, throughput, delay, and network lifetime for mobile WSNs. Conclusively, Data security is provided to reach the sink.
Link-aware and Velocity Energy-efficient Cluster-Tree, data accumulation tree, data accumulation node, cluster tree, wireless sensor networks.
M.Savitha, O.P.UmaMaheswari
The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction [1]. The Technology enables human life easier. In this context Internet of Things enables human life easier and comfort. The various countries of world utilises the technology in field of agriculture. As Agriculture is the backbone of any country survival and development. This paper deals with a survey on Internet of Things applications in agriculture in various countries.
IoT, smart agriculture, IoT applications, smart farming.
Kavitha Sooda, Archana Naik, Sanjana Vagle, Sathwik Shetty, Srinidhi B R, Shivakumar R
My Gurukul , a web-based student-faculty knowledge portal, is aimed at handling the various college activities and providing all relevant information for the respective user. As it is a generic approach to satisfy the college needs of not one but many other institutions, the requirement for a customized digital solution paved the way for the making of solution – Alphabet, a Complete Academic Solution. This solution is android based and is destined to be used as an Android application. Henceforth, it is developed using Android Studio backed up with XAMPP as a local server and MySQL as a database. The student as well as the faculty logs in the application using their unique identification (USN for students and Employee ID for faculty) and password. This work explains how the application is a one stop customized solution for college. Google’s Firebase Cloud Messaging [2] is actively used for the purpose of sending notifications. This app is more convenient for both student and faculty. The entering/viewing the attendance, marks, library book checking, ordering the photocopy of notes and books is developed in this application.
Class Attendance Update, College events, CO mapping, Virtual library
Dr.R.Hemalatha, K.Devipriya, L.Subathra devi
As the amount of data is growing day by day, there is a high requirement to extract knowledge from the data. With the growth in population and disease, there is need to include data mining in the field of health care industry. Studies have shown that cancer is one of the widespread diseases leading to fatal death today. Among them, lung cancer and breast cancer accounts the most. It has been found that if the disease is being diagnosed at an early stage, the survival rate of the patient could be improved but most of the time the disease is being diagnosed at a later stage. Deaths due to Lung cancer are about 1.4 million per year worldwide. Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of cancer prevention. However, this is a multi-layered problem. Therefore a cancer risk prediction system is here proposed which is easy, cost effective and time saving. This research paper analyzes how data mining techniques and image processing techniques are used for predicting and diagnosing major life threatening lung cancer disease.
Association rules, Clustering, Classification Cancer Survey , Data Mining , Medical Image Processing,
Babu Kumar S, Karthik S A, Divya Shree
Due to increase in the number of vehicle in the resent years, the accident count has noticeably increased. Moreover whenever an obstacle is detected in the road it is not possible to stop the vehicle immediately due to forward force and fraction of time available to react to the scenario. So in this paper a new technique is proposed using the sensors and haar features to detect the obstacles present in the road which can include the pedestrians, Lane etc. The experimental results shows that the technique used as a better efficiency in detecting the obstacle and immediately providing the signal to the driver, so that more time is available for the driver to react to the obstacle . More or the less the worst situation is to bring the vehicle to the stop mode. The method implemented here shows the efficiency of above 80% when compared to the traditional method that is available.
Pedestrians, Lane, Obstacles detection, smart sensor, haar feature