In the rapid world of technology, the IT Industry is growing at a rapid speed with Cloud Image Security. In the developing trends, cloud orchestration is becoming impressive and uncertain of dealing a large amount of information. In the last two decades there has been extensive development in image encryption. Chaos based image encryption techniques form framework for a faster algorithm than traditional techniques. Chaos based techniques are highly efficient in case of multimedia data. The proposed algorithm uses the modified logistic map for the generation of chaotic sequence, encrypts the image in single scan, so runs faster and makes the proper use of confusion and diffusion. It dynamically updates the key during execution. This algorithm is secure against the brute force attack and differential attack.

In GPS system enabled hand-held communication devices which works as a beacon that transmits our location. Also, the location-based services that emerged in recent years make use of location data. The location data provided to these location-based service providers have enough sensitive information to bother about. The location privacy became an area of concern in recent years. Developed and developing countries are now in process to make laws against the use of location information without the consent of the user or without legal warrant. Most of the research strategies proposed in recent years have one thing in common that we provide a region instead of exact coordinates of the location of the user. These attacks are called location dependent attacks or velocity linkage attacks in literature. We have in our effort proposed a solution to the problem of location privacy protection taking care of the location dependent attacks. We also keep in mind the fact that user is more concerned about his locations at certain places. We tested the proposed solution against requests issued by 5000 and 15000 users moving in a field of 10000x10000 units' area.

The amalgamation of wearable sensor technologies and artificial intelligence (AI) presents a transformative paradigm for optimising athletic performance in real time. This paper explores the integration of cutting-edge sensors - including bioimpedance sensors, accelerometers, and gyroscopes - with advanced AI algorithms such as machine learning and decision support systems. By capturing diverse physiological, biomechanical, and environmental data, the proposed framework aims to offer personalized, actionable insights for athletes. This research synthesizes the current landscape of wearable sensor technology in sports and highlights the evolving role of AI in interpreting data for enhancing athletic performance. It delineates an innovative framework designed for real-time analysis, personalized feedback, and training optimization. The seamless interaction between sensors and AI models empowers athletes and coaches to make informed decisions, optimizing training regimens and minimizing injury risks. The paper discusses the practical implications, challenges, and ethical considerations associated with this integration, emphasizing its potential benefits in diverse sports disciplines. Results from real-world trials underscore the efficacy of the proposed framework in providing dynamic guidance to athletes, thereby augmenting their performance through tailored interventions.

The primary business model of bespoke tailoring remains largely manual and offline, limiting its operating efficiency and access to market opportunities. This research details the Stitchify system, an innovative electronic solution based on the MERN(MongoDB, Express.js, React.js, Node.js) platform to connect method artisans with contemporary buyers. Stitchify follows a robust three-tier architecture to provide for various types of users that include: consumers requiring custom clothing, tailors managing custom order production capacity, and couriers responsible for managing the delivery of garments. Functionalities include scheduling of measurement sessions and scheduling of doorsteps for collection and delivery of fabric samples, tracking of orders in real time, secure payment processing, and role based access control. Load testing indicates that the system will perform well under high concurrent load; during load tests, users received responses to requests within 250ms even when 100 users were connected at the same time. Volunteer participants tested the platform's usability by completing tasks on it without previous training, and their average task completion time was less than three minutes which shows that the interface is easy to use. Along with its technical benefits, this study addresses socioeconomic difficulties experienced by sole proprietor tailoring. Professionalism is advancing with digital infrastructures that offer access to new markets, lowering the cost of entry. The research confirms the validity of the on-demand service model for craft-based businesses, as well as the measurable improvements in business transparency, business capacity, and customer satisfaction for small tailoring businesses. Keywords: Digital Transformation; MERN Stack; Bespoke Tailoring; On-Demand Services; Full-Stack Web Development; Hyperlocal Commerce; Mobile Devices; Digitization of Services.