The Internet of Things (IoT) can be defined as a network of intelligent objects where physical objects are equipped with electronic and network components to enable connectivity. These smart objects are embedded with sensors that enable them to monitor, sense, and gather data pertaining to their surroundings, including the environment and human activities. The applications of IoT, both existing and forthcoming, show great promise in terms of enhancing convenience, efficiency, and automation in our daily lives. However, for the widespread adoption and effective implementation of The Internet of Things, addressing concerns related to security, authentication, privacy, and recovery from potential attacks is crucial. To achieve end-to-end security in Internet of Things environments, it is imperative to make necessary modifications to the architecture of The Internet of Things applications. In this paper, we propose assessment parameters and a layered framework that integrates The Internet of Things and blockchain to enhance

Customer Relationship Management (CRM) is a complete approach to constructing, handling, and establishing loyal and long-lasting customer relationships. It is mostly acknowledged and widely executed for distinct domains, e.g., telecom, retail market, banking and insurance, and so on. A major objective is customer retention. The churn methods drive to recognize early churn signals and identify customers with an enhanced possibility to leave voluntarily. Machine learning (ML) techniques are presented for tackling the churning prediction difficult. This paper presents a Remora Optimization with Machine Learning Driven Churn Prediction for Business Improvement (ROML-CPBI) technique. The aim of the ROML-CPBI technique is to forecast the possibility of customer churns in the business sector. The working of the ROML-CPBI technique encompasses two major processes namely prediction and parameter tuning. At the initial stage, the ROML-CPBI technique utilizes multi-kernel extreme learning machine (MKELM) technique for churn prediction purposes. Secondly, the RO algorithm is applied for adjusting the parameters related to the MKELM model and thereby results in enhanced predictive outcomes. For validating the greater performance of the ROML-CPBI technique, an extensive range of experiments were performed. The experimental values signified the improved outcomes of the ROML-CPBI technique over other ones.

The shortcomings of conventional healthcare systems are becoming more apparent as the Internet of Things (IoT) becomes ever more pervasive in people's daily lives. The standard procedure for dealing with confidential data frequently results in unwanted public disclosure. Blockchain's agreements make it possible to automate the safe transfer of patient data based on their individual authorization settings. To create a completely untraceable trading platform, blockchain technology is frequently implemented. To protect user data in the Internet of Things (IoT), a privacy-protecting protocol is developed using the blockchain. It is important to consider that the rogue cloud server might potentially develop a database of user behaviour profiles, which could be a serious breach of privacy. Confidentiality makes it more difficult to resolve disagreements about private data exchange transactions. When users of metadata are falsely accused, their rights are difficult to defend. Also, smart contracts are used to enforce security protocols and data privacy for multisharing adaptable access control. There is no reason to doubt the safety of the proposed work. The proposed work is efficient and applicable, as demonstrated by the efficiency evaluation and experimental findings.

One of the essential parts of electrical hardware utilized in the operation of an energy system is a transformer. Transformers are monitored regularly to prevent issues that are prohibitively expensive to repair and that may result in the loss of electricity. With the distribution transformer, serving as an example of a load current, temperature, and oil level indicator, the primary objective of this article is to use the Internet of Things (IoT) to monitor and uncover errors in the distribution networks in real time. This is a unified system that keeps track of different characteristics that have an immediate bearing on the transformer. The three main challenges that contribute to the distribution transformer failure are overloading, oil temperature load current, and inadequate transformer cooling. It is challenging to manually assess the status of every transformer in the current electric networks due to the widespread distribution of the transformers. Different types of sensors are utilized in order to keep track of the temperature, oil level, current, and voltage. The microprocessor acts in response to the interpretations provided by the sensor in order to maintain a consistent working environment for the transformer. The system that has been suggested has a cheap price point, is simple to operate, and can inspect and show data using IoT.

Internet of Things (IoT) is a future internet or amendment to existing internet with surrounding things as part of a network generally defines as networked smart things, where every physical "thing" or "node" is embedded with a digital element and working in a network. Each node in IoT monitor and senses the surrounding environment to collect the data and transfer it to the application layer to derive intelligence. The level of efficiency, automation, and comfort for human life will increase through existing IoT and future IoT opportunities. To effectively implement IoT with a rapid increase in IoT applications demands privacy, promising security, and authentication for all entire transactions in the network, and the system should be able to recover from any kind of attack. This study has presented a detailed review of IoT, layer base IoT architecture, and different threats for each layer of IoT along with all possible security and privacy risks for IoT along with existing solutions with the help of blockchain. The recent emerging technology, blockchain is a transparent, trusted, and decentralized P2P network with core properties of immutability, security, and integrity. The IoT can achieve better security with blockchain integration but need to address various challenges. This paper also presented various possible IoT and Blockchain integration for promising security and privacy.