Empowering Cybersecurity: A Deep Dive into AI-Driven Security Intelligence Modelling
Smart Incubator for Empowering Poultry Farmers by Maximizing Egg Hatching Success
Early Disease Detection of Black Gram Plant Leaf using Cloud Computing Based YOLO V8 Model
Data Retrieval in Cancer Documents using Various Weighting Schemes
Securing Healthcare Data in Smart Cities: A Machine Learning Approach
Radio frequency identification (RFID) is the generic term for technologies involving radio waves to identify tagged objects and collect data. From corporate sector to defense, and from medicine to farming, today RFID is finding a wide range of application. India is increasingly becoming a manufacturing hub of goods and services for the U.S and the European nations whose own supply chains are equipped with RFID. This has forced the Indian manufacturers to adopt RFID technology. Analysts believe that the RFID market in India will grow beyond 
100 crores by 2014-15. This paper presents the issues and challenges that are faced in adopting RFID technologies in India. The study finds that there are a lot of hindrances such as the high implementation costs, low RFID awareness, lack of R&D in RFID technologies, lack of clarity on cost and profit sharing and issues relating to privacy that presents a great amount of challenge for wide scale application of RFID in India.
Developing software systems has become the fastest, most perfect and affordable way of approaching problems using information technology and deriving the best of all possible solutions to meet customer’s needs in this world of globalization. This research is an analysis and implementation of a computerised system that is going to be used at the UDS in the comp sci. Dept. This is to minimize drastically the numerous challenges associated with the manual system that is currently in use. This system is programmed to connect to an SQL Server which holds the database that serves as the backend data storage for the system. This software basically stores details of student registration and examination result information. It as well stores information of lecturers in the department. This system can be used to create backup files for the database to prevent data loss when events such as illegal alterations of data and natural disaster occur.
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. In typical data mining systems, the mining procedures require computational intensive computing units for data analysis and comparisons. A computing platform is, therefore, needed to have efficient access to, at least, two types of resources: data and computing processors. For small scale data mining tasks, a single desktop computer, which contains hard disk and CPU processors, is sufficient to fulfill the data mining goals. Indeed, many data mining algorithm are designed for this type of problem settings. For medium scale data mining tasks, data are typically large (and possibly distributed) and cannot be fit into the main memory. Common solutions are to rely on parallel computing , collective mining to sample and aggregate data from different sources and then use parallel computing programming .In this paper we concentrated the Tier I i.e.,Big Data Mining Platforms by using MapReduce (MR). For this technique we follow the Distributed Aggregation for Data Parallel computing. In this technique we reduce the network traffic over the network.
Shopping Mart concerns for shopping various items and accessories offline. In shopping mart, basically customers choose the liked items from the shelves and keep it on the basket trolley and after selecting all the required items, the customer reach to the billing counter for bill all the selected items in the basket. The person in the billing counter pick product one by one, from bill tray read the bar code of each item with the help of RFID and generate the bill. In the present scenario, it seems that the numbers of customers are increasing to purchase their required products from shopping mart due to the fact that all the items are availed from one roof. Even though shopping mart has many billing counters, but they cannot manage proportionate to customer arriving at billing counter and customer has to wait in anyone of the billing counter queue. This leads to wastage of time for each customer waiting in the queue, as service for each customer increases or decreases proportionate to number of products selected by each customer and in total, average service time increases. In order to avoid this situation, thought provoking idea is to automate the basket trolley with auto bill calculation of the selected products and filled in the basket by the customer so that service time reduced.
Deployed in 1990’s, Mobile Adhoc networks have been widely researched for many years. Mobile Ad-hoc Networks are a collection of two or more devices equipped with wireless communications and networking capability. These devices can communicate with other nodes that are within their radio range or one that is outside their radio range. For the later, the nodes should select an intermediate node to be the router to forward the packets from the source to the destination. In MANETs every node can act as the gateway. In this dissertation, focus is laid on energy efficiency. There are many routing protocols in MANETs like DSDV, DSR and AODV etc. and each one has its own approach for dissemination of data packets in MANETs. But these routing protocols are less energy efficient. The aim of this dissertation is to design a routing protocol which would be better than the existing ones in terms of energy utilization and delivery ratio. In this dissertation an energy efficient routing protocol has been proposed which uses Dijakstra’s algorithm as a fundamental algorithm to route the nodes to their intended destination and a comparison is laid between the proposed protocol, AODV, DSDV and DSR, and the performance measures are evaluated.
