In 2008, the emergence of the blockchain as the foundation of the first-ever decentralized cryptocurrency not only revolutionized the financial industry but proved a boon for peer-to-peer (P2P) information exchange in the most secure, efficient, and transparent manner. The blockchain is a public ledger that works like a log by keeping a record of all transactions in chronological order, secured by an appropriate consensus mechanism and providing an immutable record. Its exceptional characteristics include immutability, irreversibility, decentralization, persistence, and anonymity.

Internet of Things (IoT) is a novel design paradigm, intended as a network of billions to trillions of tiny sensors communicating with each other to offer innovative solutions to real time problems. These sensors form a network named as Wireless Sensor Networks (WSN) to monitor physical environment and disseminate collected data back to the base station through multiple hops. WSN has the capability to collect and report data for a specific application. The location information plays an important role for various wireless sensor network applications. A majority of the applications are related to location based services (LBS). The development of sensor technology, processing techniques and communication systems give rise to a development of the smart sensor for the adaptive and innovative application. So a single localization technique is not adequate for all application. In this paper, a recent extensive analysis of localization techniques and hierarchical taxonomy and their applications in the different context is presented. This taxonomy of the localization technique is classified based on presence of offline training in localization namely self determining and training dependent approaches. Finally, various open research issue related to localization schemes for IoT are compared and proposed various directions for future research.

Reducing energy consumption in the fog computing environment is both a research and an operational challenge for the current research community and industry. There are several industries such as finance industry or healthcare industry that require a rich resource platform to process big data along with edge computing in fog architecture. As a result, sustainable computing in a fog server plays a key role in fog computing hierarchy. The energy consumption in fog servers depends on the allocation techniques of services (user requests) to a set of virtual machines (VMs). This service request allocation in a fog computing environment is a nondeterministic polynomial-time hard problem. In this paper, the scheduling of service requests to VMs is presented as a bi-objective minimization problem, where a tradeoff is maintained between the energy consumption and makespan. Specifically, this paper proposes a metaheuristic-based service allocation framework using three metaheuristic techniques, such as particle swarm optimization (PSO), binary PSO, and bat algorithm. These proposed techniques allow us to deal with the heterogeneity of resources in the fog computing environment. This paper has validated the performance of these metaheuristic-based service allocation algorithms by conducting a set of rigorous evaluations.

Various commercial off-the-shelf components are available for the development of communication-enabled consumer electronics devices. This opens new doors to attackers who can take advantage of various vulnerabilities to attack the entire network and compromise the integrity of the system and the environment. If a malicious device enters the environment and the attacker gains access to the server or transmits malicious data to the server or cloud, the entire network can be jeopardized. To avoid such cases, this paper presents a device authentication scheme which uses Physical Unclonable Functions (PUFs) and is suitable for Internet-of-Medical-Things (IoMT). The main advantage of this authentication scheme is that no data related to the IoMT devices are stored in server memory. The time taken to authenticate the devices completely was 1.2 sec to 1.5 sec. A Hybrid Oscillator Arbiter Physical Unclonable Function was used for validation of the proposed authentication scheme. From the PUF module used during experimental validation, the number of keys that could be potentially used for the authentication protocol from each design is approximately 240. The proposed authentication scheme increases the robustness of the design while being lightweight to be deployed in various designs and supports scalability.

The ’Smart World’ envisioned by technology will be achieved by the penetration of intelligence into ubiquitous things including physical objects, cyber-entities, social-elements or individuals and human thinking. The development of Smart World is enabled by diverse applications of Wireless Sensor Networks (WSN) into those components identified as things. Such a smart-world will have features controlled significantly by the location information. Control and Policy information of Smart World services, often addressed as Location-Based Services (LBS), are governed by location data. Localization thus becomes the key enabling technology for Smart World facilities. It is generally classified as active and passive techniques in nature. Active localization is a widely adopted localization scheme where the target is detected and tracked carries a tag or attached device. The other category, Passive methods, defines targets to be localized as free of carrying a tag or device, hence also referred to as Device-Free localization (DFL) or Sensor-less localization. The passive approach is a well suited for the development of diverse smart world applications with ubiquitous localization. Device-free localization schemes fall into a wide range of application scenarios within the Smart World ecosystem. A few notable examples are occupancy detection, identity definition, positioning, gesture detection, activity monitoring, pedestrian and vehicle-traffic flow surveillance, security safeguarding, ambient intelligence-based systems, emergency rescue operations, smart work-spaces and patient or elderly monitoring. In this paper, the revolution of device-free localization technologies have been reviewed and classified comprehensively. Further, the emergence of the Smart World paradigm is analyzed in the context of device-free localization principles. Moreover, the inherent challenges within the application domains have been extensively discussed and improvement strategies for multi-target localization and counting approach are discussed. Finally, current trends and future research directions have been presented.

This paper reviews different types of conversational agents used in health care for chronic conditions, examining their underlying communication technology, evaluation measures, and AI methods. A systematic search was performed in February 2021 on PubMed Medline, EMBASE, PsycINFO, CINAHL, Web of Science, and ACM Digital Library. Studies were included if they focused on consumers, caregivers, or healthcare professionals in the prevention, treatment, or rehabilitation of chronic diseases, involved conversational agents, and tested the system with human users. The search retrieved 1087 articles. Twenty-six studies met the inclusion criteria. Out of 26 conversational agents (CAs), 16 were chatbots, seven were embodied conversational agents (ECA), one was a conversational agent in a robot, and another was a relational agent. One agent was not specified. Based on this review, the overall acceptance of CAs by users for the self-management of their chronic conditions is promising. Users’ feedback shows helpfulness, satisfaction, and ease of use in more than half of included studies. Although many users in the studies appear to feel more comfortable with CAs, there is still a lack of reliable and comparable evidence to determine the efficacy of AI-enabled CAs for chronic health conditions due to the insufficient reporting of technical implementation details.