A framework based IOHT for comprehensive, intelligent, and adaptive solution in the health domain

Abstract

Life and happiness are directly related to health, so we can state that nothing is more important. The healthcare system and its improvements serve as key indicators of social progress and the level of care for individuals. Therefore, the healthcare sector has attracted significant attention from researchers after the digital revolution and important advancements in technological tools. One of the latest technologies and concepts is the Internet of Healthcare Things (IoHT) / Internet of Medical Things (IoMT), which acts as an umbrella for all stages of development in this sector, starting from E-Health, then M-Health, S-Health, followed by I-Health, U-Health, and finally reaching IoHT. Even though IoHT has introduced many smart applications based on the Internet of Things and artificial intelligence, all healthcare systems, even the most advanced ones, faced challenges during the real test of the COVID-19 pandemic. This thesis analyzes the challenges faced by healthcare systems based on IoHT. These challenges have impacted the ability of systems to deal with pandemics, affected the effectiveness of healthcare systems, and threatened their future. The thesis addresses the different challenges that are extremely important, given the sector in which they are applied, i.e. the health field. The challenges addressed are: 1- The most significant challenge is the lack of a comprehensive unified platform or framework in the healthcare sector. Instead, there are thousands of independent services, applications, and systems addressing various health-related issues or problems. 2- Providing reliable real-time data from different sources to ensure effective solutions through the utilization of data science, artificial intelligence, algorithms, and associated models. 3- Performance and responsiveness to emergency cases, requiring computational power to process large volumes of data generated from various data sources. 4- Availability of services and mobility regardless of circumstances. 5- Interoperability at the device, service, protocol, and heterogeneous data levels, hindering the ability to collaborate and integrate various healthcare services and systems. 6- Data security and reliability, a major issue for all modern technologies, gaining importance with the sensitivity of healthcare data and services. 7- Data privacy, is one of the biggest challenges in the healthcare sector due to the nature of data and its significant connection to users, in addition to the need to maintain the accuracy of healthcare data while protecting it. 8- Pandemics, revealed weaknesses in healthcare systems' response to pandemics and the absence of specific protocols for pandemic management. 9- Mass gatherings health, not adequately addressed despite a significant increase in large-scale events in recent years across various domains (religious, cultural, political), complicating matters during pandemics and resulting in the deaths of thousands. 10- Special attention to people with disabilities, the elderly, and those with chronic diseases, as they require special services and treatment to create effective systems enabling them to lead their daily lives normally. 11- Society and the environment, with little focus on community awareness and the need to address issues of pollution, energy, and plant and animal health. We wanted our thesis to be a humanitarian message addressing all the previous points, not just focusing on one aspect. To ensure the validity of our claim in the main message goal, which is to build a comprehensive framework based on IoHT to create effective and resilient healthcare systems capable of withstanding pandemics and other challenges while ensuring the security and privacy of its users. As part of the sub-objectives of the message, we worked extensively and in-depth on the eleven aforementioned challenges. We reviewed existing solutions for each challenge, discussed their weaknesses, and presented our solution in a way that does not negatively impact other challenges. To address the first, second, third, and fourth challenges, we designed a comprehensive framework consisting of five integrated layers, each layer having its elements and functions that collectively contribute to solving one or more challenges. Most modern technologies have been employed in the proposed framework, including but not limited to (Internet of Things, Crowdsourcing, Computing models, Drones, Smart phones and smart devices, Data sciences and Artificial Intelligent Algorithms). • The first layer was the Sensing Layer responsible for providing data from multiple sources (IoT devices such as RFID tags or wireless mesh sensors, wearable sensors, smartphones, social media, and crowdsourcing from users themselves to provide real-time data from everywhere, in addition to data from healthcare systems, applications, and services). • The second layer was Fog Computing to alleviate the burden on the cloud by performing initial data processing locally and providing real-time response without delay, especially in emergencies. The integration between fog and cloud computing had a positive impact in mitigating all other challenges, especially availability and mobility. • The third layer was a proposed Intermediate Computing layer called Light Cloud, stronger than fog and faster than the cloud, to better distribute the workload create Federated Learning for aggregated data and better manage fog nodes. Additionally, this layer supports Mobility by providing mobile edge facilities and relying on drones in many services. • The fourth layer is the Cloud responsible for aggregating all data from the other layers and providing immense computing power to execute data science algorithms, including data mining, machine learning, text mining, and deep learning, in addition to artificial intelligence algorithms and tools. This layer has contributed to preserving data permanently to form historical data that, through analysis, can yield a wealth of knowledge and rules supporting healthcare management and government decisions, as well as improving the adaptability and intelligence of healthcare services. • The fifth layer is the Services and Applications layer, and the concept of a Super App for Health has been proposed, where all healthcare services can be provided through one comprehensive application. The Super App will contribute to creating fair competition among service providers to deliver better quality services, enabling Auto-Selection for the best service for the user based on their preferences, context, service quality, and evaluation. The solution of the fifth challenge, interoperability and resolving the issue of heterogeneous data, involved categorizing all solutions proposed in the field of interoperability in a survey. Solutions spanned all levels of interoperability (hardware, protocols, formats and syntax, databases, data, and semantics). In reality, there is no single comprehensive solution, so we proposed a hybrid approach integrating multiple solutions, along with suggesting the design of a comprehensive ontology to unify new systems and services and support interoperability between them. For legacy systems, a service based on TM was proposed to transform messages from these systems to align with the Ontology. The sixth challenge, data security, and trustworthiness saw the best-proposed solutions in previous research relying on Blockchain. However, the challenge was that current consensus algorithms were not suitable for operation during pandemics. Therefore, a survey of consensus algorithms was conducted, leading to the proposal of a new consensus algorithm called Proof of Reputation, suitable for healthcare services, providing trustworthy data that is tamper-proof and non-repudiable. Additionally, the decentralized nature of blockchain was compatible with fog computing, offering a higher level of data protection. Furthermore, for highly sensitive and confidential data, a new lightweight and highly secure obfuscation method was proposed, surpassing other methods in terms of trust, robustness, performance, and resistance to attacks. The seventh challenge, data privacy, involved reviewing all major approaches to privacy protection and their associated methods such as Dummy, obfuscation, Third Trusted Party, Cloak Area, Mix Zone, Private Information Retrieval, and Encryption. All these methods suffer from drawbacks related to their impact on data accuracy or performance, which is unacceptable in the healthcare sector. A special approach to privacy protection was proposed that preserves data accuracy without a significant impact on performance. Additionally, a specific approach for privacy protection of Crowdsourcing data was suggested to encourage users and volunteers to contribute to data provision while maintaining privacy. The eighth challenge, specifically addressing pandemics, proposed a special protocol for operation within this framework. The protocol considers providing specialized services and supporting early warnings to take necessary precautions through threat-level classification algorithms or infection assessment. Additionally, it emphasizes the role of mobile health centers, remote healthcare services, and reliance on drones and volunteers, as well as enhancing health awareness and social distancing during pandemics. All of the above was implemented while ensuring the reliability of aggregated data, preventing rumors during pandemics, and preserving individuals' privacy. The ninth challenge is enhancing health and safety during gatherings. Previous research has predominantly focused on addressing crowd congestion and safety more than health concerns. However, following COVID-19, the importance of health measures within crowds became evident, necessitating solutions for effectively managing crowds while ensuring both health and safety. Integration of various solutions within a general framework was proposed, along with a specialized lightweight monitoring algorithm based on ML and TM. Additionally, smart sanitization and smart alert solutions were suggested, along with a mobile application to provide services specifically for participants in gatherings. Smart gates and digital pathways were also proposed for effectively controlling crowd flow. The tenth challenge involves catering to individuals with special needs by allocating a set of services tailored to them, along with early detection services for chronic diseases and services for the elderly and children as well. The eleventh challenge focuses on community and environmental care. A platform to support community health awareness with a search engine for health issues (diseases, health centers, medications, and health articles) was proposed. Additionally, an application was developed to manage the blood donation process and provide timely blood supply. Furthermore, a service to promote volunteering in first aid was introduced. Moreover, efforts are underway to enhance plant health, and a platform for waste management and pollution reduction is being developed. Finally, we pointed out some future work and areas where further contributions can be made to provide additional solutions.