Internet of Things (IoT) is now in its initial stage but very soon, it is going to influence almost every day-to-day items we use. The more it will be included in our lifestyle, more will be the threat of it being misused. There is an urgent need to make IoT devices secure from getting cracked. Very soon IoT is going to expand the area for the cyber-attacks on homes and businesses by transforming objects that were used to be offline into online systems. Existing security technologies are just not enough to deal with this problem. Blockchain has emerged as the possible solution for creating more secure IoT systems in the time to come. In this paper, first an overview of the blockchain technology and its implementation has been explained; then we have discussed the infrastructure of IoT which is based on Blockchain network and at last a model has been provided for the security of internet of things using blockchain.

In this review article, we survey the current state of art of printed nanomaterial systems and their future prospects.

Burn is one of the serious public health problems. Usually, burn diagnoses are based on expert medical and clinical experience and it is necessary to have a medical or clinical expert to conduct an examination in restorative clinics or at emergency rooms in hospitals. But sometimes a patient may have a burn where there is no specialized facility available, and in such a case a computerized automatic burn assessment tool may aid diagnosis. Burn area, depth, and location are the critical factors in determining the severity of burns. In this paper, a classification model to diagnose burns is presented using automated machine learning. The objective of the research is to develop the feature extraction model to classify the burn. The proposed method based on support vector machine (SVM) is evaluated on a standard data set of burns-BIP_US database. Training is performed by classifying images into two classes, i.e., those that need grafts and those that are non-graft. The 74 images of test data set are tested with the proposed SVM based method and according to the ground truth, the accuracy of 82.43% was achieved for the SVM based model, which was higher than the 79.73% achieved in past work using the multidimensional scaling analysis (MDS) approach.

Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the world have taken a keen interest in this issue and finally introduced the concept of the smart grid. Smart grid is an ultimate solution to all of the energy related problems of today’s modern world. In this paper, we have proposed a meta-heuristic optimization technique called the dragonfly algorithm (DA). The proposed algorithm is to a real-world problem of single and multiple smart homes. In our system model, two classes of appliances are considered; Shiftable appliances and Non-shiftable appliances. Shiftable appliances play a significant role in demand side load management because they can be scheduled according to real time pricing (RTP) signal from utility, while non-shiftable appliances are not much important in load management, as these appliances are fixed and cannot be scheduled according to RTP. On behalf of our simulation results, it can be concluded that our proposed algorithm DA has achieved minimum electricity cost with a tolerable waiting time. There is a trade-off between electricity cost and waiting time because, with a decrease in electricity cost, waiting time increases and vice versa. This trade-off is also obtained by our proposed algorithm DA. The stability of the grid is also maintained by our proposed algorithm DA because stability of the grid depends on peak-to-average ratio (PAR), while PAR is reduced by DA in comparison with an unscheduled case.

The Intelligent vehicle is experiencing revolutionary growth in research and industry, but it still suffers from a lot of security vulnerabilities. Traditional security methods are incapable of providing secure IV, mainly in terms of communication. In IV communication, major issues are trust and data accuracy of received and broadcasted reliable data in the communication channel. Blockchain technology works for the cryptocurrency, Bitcoin which has been recently used to build trust and reliability in peer-to-peer networks with similar topologies to IV Communication world. IV to IV, communicate in a decentralized manner within communication networks. In this paper, we have proposed, Trust Bit (TB) for IV communication among IVs using Blockchain technology. Our proposed trust bit provides surety for each IVs broadcasted data, to be secure and reliable in every particular networks. Our Trust Bit is a symbol of trustworthiness of vehicles behavior, and vehicles legal and illegal action. Our proposal also includes a reward system, which can exchange some TB among IVs, during successful communication. For the data management of this trust bit, we have used blockchain technology in the vehicular cloud, which can store all Trust bit details and can be accessed by IV anywhere and anytime. Our proposal provides secure and reliable information. We evaluate our proposal with the help of IV communication on intersection use case which analyzes a variety of trustworthiness between IVs during communication.