The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic.

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IoT-Based Applications in Healthcare Devices.

Analyzing patient health information based on IoT sensor with AI for improving patient assistance in the future direction

Human Intelligence is considered superior compared to Artificial Intelligence (AI) because of its ability to adapt faster to changes. Due to increasing data deluge, it is cumbersome for humans to analyse the vast amount of data and hence AI systems are in demand in today's world. However, these AI systems lack self-awareness, social skills, multitasking and faster adaptability. Cognitive Computing (CC), a subset of AI, acts as an effective solution in solving these challenges by serving as an important driver for knowledge-rich automation work. Knowing the latest research and state of the art in CC is one of the initial steps needed for researchers to make progress in this front. Thus, this paper presents a comprehensive survey of prior research in the CC domain along with the challenges, solutions and future research directions. Specifically, CC-based techniques solving real-world problems in four widely-researched application areas, namely, healthcare, cybersecurity, big data and IoT, have been reviewed in detail and the open research issues are discussed. 

Application of cognitive computing in healthcare, cybersecurity, big data and IoT: A literature review

Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of healthcare, has enabled the caretakers and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. The role of medical big data becomes a challenging task in the form of storage, required information retrieval within a limited time, cost efficient solutions in terms care, and many others. Early decision making based healthcare system has massive potential for dropping the cost of care, refining quality of care, and reducing waste and error. Scientific programming play a significant role to overcome the existing issues and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Therefore, to address this problem efficiently a detailed study and analysis of the available literature work is required to facilitate the doctors and practitioners for making the decisions in identifying the disease and suggest treatment accordingly. The peer reviewed reputed journals are selected for the accumulated of published research work during the period ranges from 2015 – 2019 (a portion of 2020 is also included). A total of 127 relevant articles (conference papers, journal papers, book section, and survey papers) are selected for the assessment and analysis purposes. The proposed research work organizes and summarizes the existing published research work based on the research questions defined and keywords identified for the search process. This analysis on the existence research work will help the doctors and practitioners to make more authentic decisions, which ultimately will help to use the study as evidence for treating patients and suggest medicines accordingly.

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A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming

Machine learning and artificial intelligence in the service of medicine: Necessity or potentiality?

A cognitive technology based healthcare monitoring system and medical data transmission

Hit and Run cases has become more common on Indian roads now a days, where one vehicle hits another and absconds away from the accident spot. Over 30% of the accidents that happen in Indian roads are Hit and Run cases. These cases keep increasing as the number of vehicle usage keeps increasing at a faster rate. In order to prevent the drivers from escaping these sorts of incidents, a system is devised which spots the accident and turns off the engine within few seconds of the accident. The system also intimates the details of the vehicle owner to nearby police station. Our system also facilitates in sending the vehicle details along with the accident spot location to the insurance company which supports them in identifying the correct reasons for the accident.

IoT based Smart Accident Detection [ISAD] System for Hit and Run Cases

In conventional modern vehicles, the Internet of Things-based automotive embedded systems are used to collect various data from real-time sensors and store it in the cloud platform to perform visualization and analytics. The proposed work is to implement computer vision-aided vehicle intercommunication V2V (vehicle-to-vehicle) implemented using the Internet of Things for an autonomous vehicle. Computer vision-based driver assistance supports the vehicle to perform efficiently in critical transitions such as lane change or collision avoidance during the autonomous driving mode. In addition to this, the main work emphasizes observing multiple parameters of the In-Vehicle system such as speed, distance covered, idle time, and fuel economy by the electronic control unit are evaluated in this process. Electronic control unit through brake control module, powertrain control module, transmission control module, suspension control module, and battery management system helps to predict the nature of drive-in different terrains and also can suggest effective custom driving modes for advanced driver assistance systems. These features are implemented with the help of the vehicle-to-infrastructure protocol, which collects data through gateway nodes that can be visualized in the IoT data frame. The proposed work involves the process of analyzing and visualizing the driver-influencing factors of a modern vehicle that is in connection with the IoT cloud platform. The custom drive mode suggestion and improvisation had been completed with help of computational analytics that leads to the deployment of an over-the-air update to the vehicle embedded system upgradation for betterment in drivability. These operations are progressed through a cloud server which is the prime factor proposed in this work.

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M. Arun Kumar

Papers

A cognitive technology based healthcare monitoring system and medical data transmission

IoT based Smart Accident Detection [ISAD] System for Hit and Run Cases

Advanced Driver Assistance System Based on IoT V2V and V2I for Vision Enabled Lane Changing with Futuristic Drivability