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
The important of any research is to address fundamental problems combating society. Research shows that the average student misplaces one item or the other, during their stay in any institution. Challenges encountered by individual and security bodies to find the lost item tends to rise and becomes more tedious. The lost item can cause depression to the student and finding the identity of the individual when the lost item is found is also challenging. The objective of this study is to develop an online lost item recovery application, that can assist students to easily search the lost items via any internet enabled device, and also the students who help to find the items can help to upload details of the items found via the internet. Thus, it is important to find an approach through the use of information technology to find the solution for issue related to misplace item in higher institutions, which in turn can foster integrity, transparency and good character among students.
Under Government of Karnataka, 15 organizations are registered as organic federations. The Tumkur District Regional Co-operative Organic Farmers Organization Federation (TDRCOFOF) is one among the registered federations. Current operations of the federation are managed by entering data in an Excel sheet and flow of information is carried out through telephonic calls. As a result of unorganized flow of information, the federation is unable to forecast or guarantee the customer about delivery of products at specific date due to lack of data about the type of crops, quantity and harvest period. To address this issue, a thorough analysis of the data flow management of the federation was carried out, which revealed the gap in seamless communication and lack of a dashboard system for decision making. Hence, an application has been designed for achieving a seamless communication between the farmers, federation and customer. For the application design process, Object Oriented Analysis and Design (OOAD) and Structured System Analysis and Design (SSAD) tools were screened and OOAD was chosen due to its cost-effectiveness and ease of use. After implementing the application, the generation of reports happen in less than 5 minutes, with substantial data for decision making and strategize business operations.
The Internet of Things (IoT) is acknowledged as a transformative technology that brings smart revolutions in all sectors of human life, industry, agriculture, healthcare, retail and much more. In fact, no IoT application do exist as a complete one promising and involving all necessary enabling technologies till now. The lack of true IoT ecosystem till date is the only cause for the fragmented nature of IoT applications, which needs to address various challenges in availability, data storage, integration, performance, processing, reliability, security and privacy issues. This work presents a comprehensive framework that imposes a true IoT ecosystem with solutions to above mentioned challenges through associating human body ecosystem with major enabling technologies of IoT. To arrive such futuristic framework, researchers’ contribution on reputed journals on these techniques and internet survey reports over trends in recent technologies are being intensively investigated. Spotlights on the environmental issues need to focus on applying the IoT applications over the society presented with a sense of achieving sustainable development by incorporating renewable and recyclable resources.
The nodes are an important prerequisite for a trustworthy network. Low cost and simplicity are initiated through consecutively trustworthy code, which can help easy attestable node into the network. A close cooperation between the System-on-Chip (SoC) software producer and device producer is needed, as unbreakable trust chain among hardware and software with Trust Anchor module (TAm) that lives in SoC for a demonstrable trusted boot. The root public signing key inside a One Time Programmable (OTP) block makes up the physical trust anchor. For instance, the device producer needs to verify and recognize the SoC manufacturer, which is not practically possible for small device producers in each and every case. A small expedient producer can yield products with safe boot using the standard procedure. With huge producers, they are capable of ordering huge count of SoC using the means of self-programmed trust anchor. TrustZone by ARM, which is a Trusted Execution Environment (TEE), gives enough protection to local verification software, as the software performed in TEE need to be appropriately signed in such a way the software comes through the producer of SoC or through any authorized producer. A study of dissimilar approaches on above topic and their pros and cons are discussed in the paper. As an outcome, this paper gives the results of each methodology and suggests better procedure to overcome the existing drawbacks.
Data fusion is a multidisciplinary research area with a boundless range of applications in numerous domains including defense, robotics, automation, Intelligent Transportation Systems (ITS), IoT and machine learning. Detection and tracing of a moving object is a vital task in mobile robotics as well as in the field of ITS. Due to its critical role, data fusion has been extensively studied in the recent decades. Computational Intelligence would become the challenging factor to integrate real time data generated from various sensory nodes to implement Internet of Things (IoT) products such as Smart Agriculture, Smart City, Smart Wheel Chair, Smart Healthcare System, etc. The methods discussed under Data Fusion methods are Kalman Filter and Distributed Kalman Filter. Deep learning and neural network-based fusion at symbol level is analyzed in this paper. This paper also aims to provide high level future research directions of data fusion techniques for Internet of Things environment.
