The advent of autonomous vehicles is indeed a potential field of research in today's situation. Connected Vehicles (CV) have received a lot of attention in the last decade, which has resulted in CV as a Service (CVaaS). With the advent of taxi services, there is a need for or demand for robust, seamless, and secure information transmission between the vehicles connected to a vehicular network. Thus, the concept of vehicular networking is transformed into novel concept of autonomous and connected vehicles. These autonomous vehicles will serve as a better experience by providing instant information from the vehicles via congestion reduction. The significant drawback faced by the invention of autonomous vehicles is the malicious floor of intruders, who tend to mislead the communication between the vehicles resulting in the compromised smart devices. To address these concerns, the best methodology that will protect and secure the control system of the autonomous vehicle in real time is blockchain. This research work proposes a blockchain framework in order to address the security challenges in autonomous vehicles. This research work enhances the security of smart vehicles thereby preventing intruders from accessing the vehicular network. To validate the suggested technique, money security criteria such as changing stored user ratings, probabilistic authentication scenarios, smart device compromise, and bogus user requests were employed. The observed findings have been documented and analysed, revealing an 82% success rate.

In Internet of Things (IoT) based systems, the multi-level user requirements are satisfied by the integration of communication technology with distributed homogeneous networks termed as the ubiquitous computing systems (UCS). The PCS demands openness in heterogeneity support, management levels and communication for distributed users. However, providing these features is still a major challenge. In wearable IoT (WIoT) based medical sensors based applications, the end users reliability of communication is enhanced using a scalable distributed computational framework introduced in this paper. The demand and sharing parameters forms the basis of analysis of resource allocation by means of recurrent learning in this framework. The rate of communication may be improved while reducing the time delay for the end users of WIoT based medical sensors with the help of UCS and estimated resource requirements. Other than data transfer, sharing and resource allocation, end-user mobility management may also be performed on the WIoT medical sensors using the proposed framework. Certain metrics are used for proving the consistency of the framework that are assessed with the help of experimental analysis and performance estimation. Parameters inclusive of storage utilization, bandwidth, request backlogs, requests handled, request failure and response time are estimated. Reduced response time, backlogs and request failure with improved storage utilization, bandwidth and requests handled are evident using the proposed framework when compared to the existing models.

Smart Cities, Homes and Communities are the spaces where IoT sensors are used to the fullest in the Utilities sector. Advanced Metering Infrastructure (AMI) providing the peer-to-peer communication between metering equipment that reads, calculate and provides the information related to distribution and measure the consumption. This paper outlines the network monitoring and management architecture that can be used in Smart Cities, homes and communities using the integrated IoT and Blockchain technology. Blockchain technology provides trustworthy resource monitoring of utilities for all members of the smart community that in-turn benefit the members of smart communities with enhanced monitoring and optimize the consumption of resources in protected and transparent way.

Big-data analytics being a useful technique in the analyzing the deeper values hidden inside a huge set of data flow that are generated in our day today lives, has almost become more prominent in variety of applications such as industrial development, smart home to smart city development and security management etc., despite its high potentials the challenges incurred makes it insufficient with certain applications that include a real time monitoring, so the paper proposes the real time monitoring of the developing manufacturing industry by proffering the intelligent big data analytics and cloud computing to present with the maximum possible insights to improvise the process of the manufacturing , by retaining the product consistency, optimal throughput and increasing the productivity.

Routing and mobile data traffic management is a major performance affecting issue in vehicular Ad Hoc networks (VANET). High-rise structures and such radio obstacles cause trouble in proper reception of signals when position-based routing schemes are used. Other major challenges include constrained mobility and irregular distribution of vehicular nodes. A stochastic mobile data traffic model is presented in this paper. This model offers security, reliability, safety and comfort for driving by overcoming the problems of traffic congestion, interference and jamming. It also addresses the handover (HO) issue that occurs during fast mobility. Along with this, the quality parameters of the system such as throughput, packet delivery ratio and delay are also evaluated.