With the proliferation of Information and Communication Technology (ICT) in every walks of the society, including healthcare services; digitization and increased sophistication have been gaining pace. With increased patient volumes recording and management of patients data digital healthcare alternatives, particularly, Electronic Healthcare Record (EHR) has gained prominence. However, traditional EHR based systems are plagued by data loss risks, security and immutability consensus over health records, gapped communication among constituted hospitals, inefficient clinical data retrieval systems among others. Blockchain has been developed as a decentralized technology that holds the promise to address the aforesaid facilities in EHR based systems. This paper presents a patient-centric design of a decentralized healthcare management system with blockchain based EHR using javascript based Smart Contracts. A working prototype based on hyperledger fabric and composer technology has also been implemented that guarantees the security of proposed model. Experiments with the hyperledger caliper benchmarking tool provides performance of metrics such as latency, throughput, resource utilization and so on under varied scenarios and control parameters and the results affirm the efficacy of the proposed approach.

In recent years, the growth rate of Cloud computing technology is increasing exponentially, mainly for its extraordinary services with expanding computation power, the possibility of massive storage, and all other services with the maintained quality of services (QoSs). The task allocation is one of the best solutions to improve different performance parameters in the cloud, but when multiple heterogeneous clouds come into the picture, the allocation problem becomes more challenging. This research work proposed a resource-based task allocation algorithm. The same is implemented and analyzed to understand the improved performance of the heterogeneous multi-cloud network. The proposed task allocation algorithm (Energy-aware Task Allocation in Multi-Cloud Networks (ETAMCN)) minimizes the overall energy consumption and also reduces the makespan. The results show that the makespan is approximately overlapped for different tasks and does not show a significant difference. However, the average energy consumption improved through ETAMCN is approximately 14%, 6.3%, and 2.8% in opposed to the random allocation algorithm, Cloud Z-Score Normalization (CZSN) algorithm, and multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS), respectively. An observation of the average SLA-violation of ETAMCN for different scenarios is performed.

This paper deals with measuring the Air Quality using MQ135 sensor along with Carbon Monoxide CO using MQ7 sensor. Measuring Air Quality is an important element for bringing awareness to take care of the future generations and for a healthier life. Based on this, Government of India has already taken certain measures to ban Single Stroke and Two Stroke Engine based motorcycles which are emitting high pollution. We are trying to implement a system using IoT platforms like Thingspeak or Cayenne in order to bring awareness to every individual about the harm we are doing to our environment. Already, New Delhi is remarked as the most pollution city in the world recording Air Quality above 300 PPM. We have used easiest platform like Thingspeak and set the dashboard to public such that everyone can come to know the Air Quality at the location where the system is installed. Machine Learning analysis brings us a lot of depth in understanding the information that we obtained from the data. Moreover, we are proviing a reducement of the cost of components versus the state of the art.