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Whenever there is too much information out there, it is desirable to summarize. If humans are trying to create the summary, it will take lot of time. Now to make the problem of summarizing information easier and more effortless one can automate the summarization process which can reduce the time taken in creating summary. This is called as automatic summarization. The two ways of summarization are extractive summarization and abstractive summarization. Extractive summarization and its applications have been the subject of extensive research and have received state of art solution. But abstractive summarization still is a progressive field as it is difficult to create abstractive summary as humans do. Also, it is still a question i.e., how to evaluate the quality of a summary? Therefore, this paper is a comprehensive survey on the dataset used with its details and statistics, analysis of various abstractive summarization techniques and important parameters for evaluating the quality of summary. Deep leaning based models have given new direction in this field. The author also focuses on problems and challenges faced in the generation of summary which are opening the future research scope in this domain. [ABSTRACT FROM AUTHOR]

In daily life, vitamins fruits and vegetables play a very important role in human life. The farmer produces grains or vegetables in huge quantities. Due to lack of storage problem farmer suffers. It is necessary to store all these things in a special warehouse. Thus, improper storage of grains or fruits is essential to meet the increasing demands. Storage time and fruit quality are greatly influenced by storage environmental factors. Therefore, it is important for the fruit storage environment to perform multi-parameter monitoring and analyze the collected parameters and then regulate and control. The quality of grains and other perishable goods kept in a warehouse usually deteriorates due to lack of monitoring and proper maintenance of their required suitable conditions in such a large area. The proposed methodology deals with the storage of grains, fruits, etc., and to identify their temperature and humidity patterns so that they will not be degraded. Establishing the environment in relation to the nature of the crop so as to determine an optimum threshold with an appropriate pattern of monitoring and change. The main goal of this research article is to provide solutions to prevent rotting of grains and fruits in the storage area. [ABSTRACT FROM AUTHOR]

In this paper, the authors have amplified the concept that EHRs need to be patient-centric and patient-driven, that is the patient should be the real owner as well as the manager of his medical records. The authors propose patient-centric multichain healthcare record (PCMHR) that implements health records using smart contracts on ethereum blockchain and also utilizes the multichain framework - Polygon. PCMHR can concurrently implement blockchain functionality while addressing the concerns of interoperability among authorized hospitals and patient health information confidentiality that damages our healthcare system. The authors propose a solution to fully decentralize the current medical healthcare system by storing PCMHR on IPFS (InterPlanetary File System) to resolve the limitation of blockchain-based applications in scalability and high cost. The authors have depicted the cost and time analysis of transactions on the polygon framework to give a clear view of this multichain framework and its advantages over the ethereum blockchain. [ABSTRACT FROM AUTHOR]

Healthcare delivery is on the verge of a fundamental shift into the new era of smart and connected health care, termed Health Care 4.0. Sharing healthcare data is an important step in improving the healthcare system's intelligence and service quality. Healthcare data, which is a personal asset of the patient, should be owned and managed by the patient rather than being dispersed among several healthcare systems, preventing data exchange and jeopardizing patient privacy. EHRs (electronic health records) assist individuals by allowing them to combine and manage their medical data. On the other hand, today's EHR systems fall short of providing patients with traceable, trustworthy, and secure ownership over their medical data, creating serious security risks. In this article, the authors propose PcBEHR (patient-controlled blockchain enabled electronic health records) as a way for patients to have safe control over their data that is decentralized, immutable, transparent, traceable, and trustworthy. Decentralized interplanetary file storage (IPFS) is used in the suggested technique. [ABSTRACT FROM AUTHOR]

Information about healthcare is derived from healthcare data. Healthcare data sharing helps make healthcare systems more efficient as well as improving healthcare quality. Patients should own and control healthcare information, one of their most valuable assets, instead of letting data be spread out among health care providers differ. This protects data from being shared between healthcare systems and privacy. Public ledger accompanied by a decentralized network of peer's compromises patient has been demonstrated to be able to achieve trusted, auditable computing by blockchain. The use of access control and cryptographic primitives are insufficient in addressing modern cyber threats all privacy and security concerns associated with a cloud-based environment. In this paper, the authors proposed a lightweight blockchain technique based on privacy and security for healthcare data for the cloud system. The cost-effectiveness of our system's smart contracts is evaluated, as well as the procedures used for data processing in order to encrypt and pseudonymize patient data. [ABSTRACT FROM AUTHOR]

People like to do bird watching but to identify bird species they need help of Zoological Science. Bird watching gives health benefits which we get by enjoying nature. Species identification is a challenging task which may result in many different labels. Sometimes even experts may disagree on species. It is both difficult of humans and computers that hit the limit of visual abilities. Hence, to help the bird spectator, we have developed deep learning based algorithms using the concept of image processing that help in identifying bird species. It will recognize the input image by comparing the model with a trained model and then predict the bird species. All the details of the bird will be displayed as an output. Also, it will help us to create dataset if any image captured or uploaded by user is missing in dataset then user can add that image to dataset. [ABSTRACT FROM AUTHOR]

The supply chain is a complex network in healthcare that crosses organizational and geographical borders. The inherent complexity of such structures can introduce impurities inclusive of erroneous facts, lack of transparency, and restricted records provenance. In the healthcare business, counterfeit pills are one of the major reasons for the harmful impact on human health and also for financial losses. Thus, pharmaceutical supply chains and end-to-end tracking systems are the recent research in healthcare. In this paper, we propose blockchain based traceability of counterfeited drugs (BBTCD) that implements tracking of counterfeited drugs using smart contracts on the Ethereum blockchain. We propose a solution to fully decentralize the tracking in healthcare by storing BBTCD on IPFS (Inter Planetary File System) to provide transparency, cost-effectiveness., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)