IoT Healthcare System Research Articles

A new data clustering strategy for enhancing mutual privacy in healthcare IoT systems

In the rapidly growing era of Internet-of-Things (IoT), healthcare systems have enabled a sea of connections of physical sensors. Data analysis methods (e.g., k-means) are often used to process data collected from wireless sensor networks to provide treatment advices for physicians and patients. However, many methods pose a threat of privacy leakage during the process of data handling. To address privacy issues, we propose a mutual privacy-preserving k-means strategy (M-PPKS) based on homomorphic encryption that neither discloses the participant’s privacy nor leaks the cluster center’s private data. The proposed M-PPKS divides each iteration of a k-means algorithm into two stages: finding the nearest cluster center for each participant, followed by computing a new center for each cluster. In both phases, the cluster center is confidential to participants, and the private information of each participant is not accessible by an analyst. Besides, M-PPKS introduces a third-party cloud platform to reduce the communication complexity of homomorphic encryption. Extensive privacy analysis and performance evaluation results manifest that the proposed M-PPKS strategy can achieve high performance. In addition, it can obtain approximate clustering results efficiently while preserving mutual private data.

Wearable Internet of Things Healthcare Systems: Smart Biomedical Sensors, Wireless Connected Devices, and Real-Time Patient Monitoring

Wearable Internet of Things Healthcare Systems: Smart Biomedical Sensors, Wireless Connected Devices, and Real-Time Patient Monitoring

The Future of Healthcare Internet of Things: A Survey of Emerging Technologies

The impact of the Internet of Things (IoT) on the advancement of the healthcare industry is immense. The ushering of the Medicine 4.0 has resulted in an increased effort to develop platforms, both at the hardware level as well as the underlying software level. This vision has led to the development of Healthcare IoT (H-IoT) systems. The basic enabling technologies include the communication systems between the sensing nodes and the processors; and the processing algorithms for generating an output from the data collected by the sensors. However, at present, these enabling technologies are also supported by several new technologies. The use of Artificial Intelligence (AI) has transformed the H-IoT systems at almost every level. The fog/edge paradigm is bringing the computing power close to the deployed network and hence mitigating many challenges in the process. While the big data allows handling an enormous amount of data. Additionally, the Software Defined Networks (SDNs) bring flexibility to the system while the blockchains are finding the most novel use cases in H-IoT systems. The Internet of Nano Things (IoNT) and Tactile Internet (TI) are driving the innovation in the H-IoT applications. This paper delves into the ways these technologies are transforming the H-IoT systems and also identifies the future course for improving the Quality of Service (QoS) using these new technologies.

DITrust Chain: Towards Blockchain-Based Trust Models for Sustainable Healthcare IoT Systems

© 2013 IEEE. Today, internet and device ubiquity are paramount in individual, formal and societal considerations. Next generation communication technologies, such as Blockchains (BC), Internet of Things (IoT), cloud computing, etc. offer limitless capabilities for different applications and scenarios including industries, cities, healthcare systems, etc. Sustainable integration of healthcare nodes (i.e. devices, users, providers, etc.) resulting in healthcare IoT (or simply IoHT) provides a platform for efficient service delivery for the benefit of care givers (doctors, nurses, etc.) and patients. Whereas confidentiality, accessibility and reliability of medical data are accorded high premium in IoHT, semantic gaps and lack of appropriate assets or properties remain impediments to reliable information exchange in federated trust management frameworks. Consequently, We propose a Blockchain Decentralised Interoperable Trust framework (DIT) for IoT zones where a smart contract guarantees authentication of budgets and Indirect Trust Inference System (ITIS) reduces semantic gaps and enhances trustworthy factor (TF) estimation via the network nodes and edges. Our DIT IoHT makes use of a private Blockchain ripple chain to establish trustworthy communication by validating nodes based on their inter-operable structure so that controlled communication required to solve fusion and integration issues are facilitated via different zones of the IoHT infrastructure. Further, text{C}mathrm {sharp } implementation using Ethereum and ripple Blockchain are introduced as frameworks to associate and aggregate requests over trusted zones.

Efficient secure surveillance on smart healthcare IoT system through cosine-transform encryption

The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system.

Challenges and opportunities in IoT healthcare systems: a systematic review

In this study, the latest research articles which are involved in the Internet of Things (IoT) based healthcare system are analyzed as the IoT is growing enormously in the healthcare systems such as health monitoring, fitness programs, etc. Numerous research has been carried out in the IoT based healthcare system to improve monitoring efficiency. The architecture used in the IoT especially the cloud integrated systems are investigated in this work. The factors such as accuracy and power consumption are the important concern in the IoT, hence the research works which are involved in improving the performance of the IoT based healthcare systems are discussed. Data management methods in the IoT based healthcare system with cloud facilities are also systematically analyzed in this study. The performance of the IoT based healthcare system along with its advantages and limitations are reviewed. Most research works are efficient in detecting several symptoms and can accurately predict the diseases. The IoT based healthcare system designed especially for elders is an efficient solution in monitoring their healthcare issues. Major limitations in the existing systems are high power consumption, availability of fewer resources and security issues due to the utilization of many devices.

A Hybrid Cryptosystem to Enhance Security in IoT Health Care System

A Hybrid Cryptosystem to Enhance Security in IoT Health Care System

Smart integrated IoT healthcare system for cancer care

The emergence of the internet of things (IoT) has drastically influenced and shaped the world of technology in the contexts of connectivity, interconnectivity, and interoperability with smart connected sensors, objects, devices, data, and applications. In fact, IoT has brought notable impacts on the global economy and human experience that span from industry to industry in a variety of application domains, including healthcare. With IoT, it is expected to facilitate a seamless interaction and communication of objects (devices) with humans in the environment. Therefore, it is imperative to embrace the potentials and benefits of IoT technology in healthcare delivery to ensure saving lives and to improve the quality of life using smart connected devices. In this paper, we focus on the IoT based healthcare system for cancer care services and business analytics/cloud services and also propose the adoption and implementation of IoT/WSN technology to augment the existing treatment options to deliver healthcare solution. Here, the business analytics/cloud services constitute the enablers for actionable insights, decision making, data transmission and reporting for enhancing cancer treatments. Furthermore, we propose a variety of frameworks and architectures to illustrate and support the functional IoT-based solution that is being considered or utilized in our proposed smart healthcare solution for cancer care services. Finally, it will be important to understand and discuss some security issues and operational challenges that have characterized the IoT-enabled healthcare system.

Remote Medical Monitoring and Cloud-based Internet of Things Healthcare Systems

Remote Medical Monitoring and Cloud-based Internet of Things Healthcare Systems

Remote Authentication Schemes for Wireless Body Area Networks Based on the Internet of Things

Internet of Things (IoT) is a new technology which offers enormous applications that make people’s lives more convenient and enhances cities’ development. In particular, smart healthcare applications in IoT have been receiving increasing attention for industrial and academic research. However, due to the sensitiveness of medical information, security and privacy issues in IoT healthcare systems are very important. Designing an efficient secure scheme with less computation time and energy consumption is a critical challenge in IoT healthcare systems. In this paper, a lightweight online/offline certificateless signature (L-OOCLS) is proposed, then a heterogeneous remote anonymous authentication protocol (HRAAP) is designed to enable remote wireless body area networks (WBANs) users to anonymously enjoy healthcare service based on the IoT applications. The proposed L-OOCLS scheme is proven secure in random oracle model and the proposed HRAAP can resist various types of attacks. Compared with the existing relevant schemes, the proposed HRAAP achieves less computation overhead as well as less power consumption on WBANs client. In addition, to nicely meet the application in the IoT, an application scenario is given.

Authenticated key agreement scheme for fog-driven IoT healthcare system

The convergence of cloud computing and Internet of Things (IoT) is partially due to the pragmatic need for delivering extended services to a broader user base in diverse situations. However, cloud computing has its limitation for applications requiring low-latency and high mobility, particularly in adversarial settings (e.g. battlefields). To some extent, such limitations can be mitigated in a fog computing paradigm since the latter bridges the gap between remote cloud data center and the end devices (via some fog nodes). However, fog nodes are often deployed in remote and unprotected places. This necessitates the design of security solutions for a fog-based environment. In this paper, we investigate the fog-driven IoT healthcare system, focusing only on authentication and key agreement. Specifically, we propose a three-party authenticated key agreement protocol from bilinear pairings. We introduce the security model and present the formal security proof, as well as security analysis against common attacks. We then evaluate its performance, in terms of communication and computation costs.

Design and Implementation of a Wireless IoT Healthcare System Based on OCF IoTivity

Design and Implementation of a Wireless IoT Healthcare System Based on OCF IoTivity

MediKit : IoT Based Smart Healthcare System for Effective Supervision of Patient

Medikit - An IoT healthcare system is developed for patients, hospitals and care centers that regularly supervise the health condition and checks whether the patient has taken the prescribed medicine. The proposed work monitors patient’s vitals such as pulse rate and body temperature on real time basis. Such information will be used by the doctor to diagnose the patient remotely and prescribe optimum medication dose. Further, the Medikit system apart from collecting the data ensures that patient has taken the medicine on time. For the proposed system the authors have used Bluetooth Technology to send sensor data to a Smartphone and also to Cloud Service Platform for archiving and analysis. The information available on the Cloud can be supervised by the doctor by using a Mobile application. The mobile application also supports scheduling of medicines as per doctor’s prescription in the medical box. The comprehensive system developed, to the best of author’s knowledge, is low cost, efficient and service oriented as compared to the traditional healthcare practices and other eHealth solutions discussed.

Toward Practical Privacy-Preserving Analytics for IoT and Cloud-Based Healthcare Systems

Modern healthcare systems now rely on advanced computing methods and technologies, such as Internet of Things (IoT) devices and clouds, to collect and analyze personal health data at an unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of a privacy nightmare. In this article, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth - a personalized digital healthcare information system that is being developed and tested for disease monitoring. We analyze the data and analytic requirements for the involved parties, identify the privacy assets, analyze existing privacy substrates, and discuss the potential tradeoff among privacy, efficiency, and model quality.

Dependability evaluation of a disaster recovery solution for IoT infrastructures

The ongoing miniaturization and cost reduction of electronic devices (microprocessors, sensors, batteries, and wireless communication units) have allowed the proliferation of the Internet of Things (IoT)-based applications. Many of these applications are mission-critical (e.g., healthcare and traffic road management), in the sense that the IoT system needs to take critical decisions in real-time. Hence, these IoT systems need to be designed using effective fault-tolerant techniques like disaster recovery (DR) solutions. This work proposes a Petri net-based approach for modeling and analysis of DR solutions for IoT infrastructures. The proposed models allow assessing important DR measures, such as system availability, cost, and recovery time objective. To demonstrate the feasibility of our approach, we present a case study in which a real-world healthcare IoT system is modeled and analyzed. Besides, sensitivity analysis is carried out to assess the effects of model parameters on the system availability.

Performance Analysis of End-to-End Security Schemes in Healthcare IoT

In this paper, we analyze the performance of the state-of-the-art end-to-end security schemes in healthcare Internet of Things (IoT) systems. We identify that the essential requirements of robust security solutions for healthcare IoT systems comprise of (i) low-latency secure key generation approach using patients’ Electrocardiogram (ECG) signals, (ii) secure and efficient authentication and authorization for healthcare IoT devices based on the certificate-based datagram Transport Layer Security (DTLS), and (iii) robust and secure mobility-enabled end-to-end communication based on DTLS session resumption. The performance of the state-of-the-art security solutions including our end-to-end security scheme is tested by developing a prototype healthcare IoT system. The prototype is built of a Pandaboard, a TI SmartRF06 board and WiSMotes. The Pandaboard along with the CC2538 module acts as a smart gateway and the WisMotes act as medical sensor nodes. Based on the analysis, we found out that our solution has the most extensive set of performance features in comparison to related approaches found in the literature. The performance evaluation results show that compared to the existing approaches, the cryptographic key generation approach proposed in our end-to-end security scheme is on average 1.8 times faster than existing key generation approaches while being more energy-efficient. In addition, the scheme reduces the communication overhead by 26% and the communication latency between smart gateways and end users by 16%. Our scheme is also approximately 97% faster than certificate based and 10% faster that symmetric key-based DTLS. Certificate based DTLS requires about 2.9 times more ROM and 2.2 times more RAM resources. On the other hand, the ROM and RAM requirements of our scheme are almost as low as in symmetric key-based DTLS.

A Survey on Prescriptive Analytic Techniques Over Healthcare Data

Rapidly increased big data and very fast technical evolutions require a new analytics that is able to precisely analyze recent data and to provide directions to attain the goal. Prescriptive analytics shows difference with descriptive and predictive analytics in that it achieves opportunities or goals through various strategies plans. This technique can be applied to various fields such as Sales team assignment, Research performance enhancement, Smart electric grids and utilities, Business process optimization, IoT service provisioning and Healthcare system. This paper mainly focuses on Healthcare system to uncover additional values from health care centres using big data analytic approach. This analytic approach also helps stakeholders in healthcare sector for gathering insight from big data to optimize personal care, increases patient outcomes and prevents unnecessary healthcare spending. Understanding clinical notes and healthcare context in the right manner is the challenge. This paper discusses about data analytics in healthcare and its features, advantages and challenges. Also, this paper presents different strategies for improving immunization rate of children.

HiCH

The Internet of Things (IoT) paradigm holds significant promises for remote health monitoring systems. Due to their life- or mission-critical nature, these systems need to provide a high level of availability and accuracy. On the one hand, centralized cloud-based IoT systems lack reliability, punctuality and availability (e.g., in case of slow or unreliable Internet connection), and on the other hand, fully outsourcing data analytics to the edge of the network can result in diminished level of accuracy and adaptability due to the limited computational capacity in edge nodes. In this paper, we tackle these issues by proposing a hierarchical computing architecture, HiCH, for IoT-based health monitoring systems. The core components of the proposed system are 1) a novel computing architecture suitable for hierarchical partitioning and execution of machine learning based data analytics, 2) a closed-loop management technique capable of autonomous system adjustments with respect to patient’s condition. HiCH benefits from the features offered by both fog and cloud computing and introduces a tailored management methodology for healthcare IoT systems. We demonstrate the efficacy of HiCH via a comprehensive performance assessment and evaluation on a continuous remote health monitoring case study focusing on arrhythmia detection for patients suffering from CardioVascular Diseases (CVDs).

Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach

Current developments in ICTs such as in Internet-of-Things (IoT) and Cyber–Physical Systems (CPS) allow us to develop healthcare solutions with more intelligent and prediction capabilities both for daily life (home/office) and in-hospitals. In most of IoT-based healthcare systems, especially at smart homes or hospitals, a bridging point (i.e., gateway) is needed between sensor infrastructure network and the Internet. The gateway at the edge of the network often just performs basic functions such as translating between the protocols used in the Internet and sensor networks. These gateways have beneficial knowledge and constructive control over both the sensor network and the data to be transmitted through the Internet. In this paper, we exploit the strategic position of such gateways at the edge of the network to offer several higher-level services such as local storage, real-time local data processing, embedded data mining, etc., presenting thus a Smart e-Health Gateway. We then propose to exploit the concept of Fog Computing in Healthcare IoT systems by forming a Geo-distributed intermediary layer of intelligence between sensor nodes and Cloud. By taking responsibility for handling some burdens of the sensor network and a remote healthcare center, our Fog-assisted system architecture can cope with many challenges in ubiquitous healthcare systems such as mobility, energy efficiency, scalability, and reliability issues. A successful implementation of Smart e-Health Gateways can enable massive deployment of ubiquitous health monitoring systems especially in clinical environments. We also present a prototype of a Smart e-Health Gateway called UT-GATE where some of the discussed higher-level features have been implemented. We also implement an IoT-based Early Warning Score (EWS) health monitoring to practically show the efficiency and relevance of our system on addressing a medical case study. Our proof-of-concept design demonstrates an IoT-based health monitoring system with enhanced overall system intelligence, energy efficiency, mobility, performance, interoperability, security, and reliability.

Smart Mobile Healthcare System based on WBSN and 5G

The intelligent use of resources enabled by Internet of Things has raised the expectations of the technical as well as the consumer community. However there are many challenges in designing an IoT healthcare system, like security, authentication and exchanging data. The IoT healthcare system, is transforming everyday physical objects, medical devices that surround us into an embedded smart healthcare system. Public healthcare has been paid an increasing attention given the human population and medical expenses exponential growth. It is well known that an effective monitoring healthcare system can detect abnormalities of health conditions in time and make diagnoses according to sensing (WBSN) data. This paper propose a general architecture of a smart mobile IoT healthcare system for monitoring patients risk using a smart phone and 5G. The design of multi-protocol unit for universal connectivity. Web and mobile applications developed to meet the needs of patients, doctors, laboratories analysis and hospitals services. The system advises and alerts in real time the doctors/medical assistants about the changing of vital parameters of the patients, such as body temperature, pulse and Oxygen in Blood etc… and also about important changes on environmental parameters, in order to take preventive measures, save lives in critical care and emergency situations.