STROVE: spatial data infrastructure enabled cloud–fog–edge computing framework for combating COVID-19 pandemic

Abstract

The outbreak of 2019 novel coronavirus (COVID-19) has triggered unprecedented challenges and put the whole world in a parlous condition. The impacts of COVID-19 is a matter of grave concern in terms of fatality rate, socio-economical condition, health infrastructure. It is obvious that only pharmaceutical solutions (vaccine) cannot eradicate this pandemic completely, and effective strategies regarding lockdown measures, restricted mobility, emergency services to users-in brief data-driven decision system is of utmost importance. This necessitates an efficient data analytics framework, data infrastructure to store, manage pandemic related information, and distributed computing platform to support such data-driven operations. In the past few decades, Internet of Things-based devices and applications have emerged significantly in various sectors including healthcare and time-critical applications. To be specific, health-sensors help to accumulate health-related parameters at different time-instances of a day, the movement sensors keep track of mobility traces of the user, and helps to assist them in varied conditions. The smartphones are equipped with several such sensors and the ability of low-cost connected sensors to cover large areas makes it the most useful component to combat pandemics such as COVID-19. However, analysing and managing the huge amount of data generated by these sensors is a big challenge. In this paper we have proposed a unified framework which has three major components: (i) Spatial Data Infrastructure to manage, store, analyse and share spatio-temporal information with stakeholders efficiently, (ii) Cloud-Fog-Edge-based hierarchical architecture to support preliminary diagnosis, monitoring patients' mobility, health parameters and activities while they are in quarantine or homebased treatment, and (iii) Assisting users in varied emergency situation leveraging efficient data-driven techniques at lowlatency and energy consumption. The mobility data analytics along with SDI is required to interpret the movement dynamics of the region and correlate with COVID-19 hotspots. Further, Cloud-Fog-Edge-based system architecture is required to provision healthcare services efficiently and in timely manner. The proposed framework yields encouraging results in taking decisions based on the COVID-19 context and assisting users effectively by enhancing accuracy of detecting suspected infected people by ∼24% and reducing delay by ∼55% compared to cloud-only system.

From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management

“…IoT technology offers a range of new possibilities for an emergency response, including early detection and warning systems, real-time monitoring and response, and post-disaster communications, recovery, and reconstruction [53,54]. Furthermore, the COVID-19 pandemic has demonstrated the need for more advanced and adaptive emergency response systems that can respond quickly to rapidly changing circumstances [55,56]. IoT technology can play a key role in these efforts, enabling remote monitoring and response, contact tracing, and other critical functions.…”

“…Ghosh, S., Mukherjee, A. [55] Pandemic Response Proposed a unified framework with Spatial Data Infrastructure, Cloud-Fog-Edge based architecture, and efficient data-driven techniques for data analytics, management, and decision making to combat pandemics such as COVID-19.…”

STOPPAGE: Spatio‐temporal data driven cloud‐fog‐edge computing framework for pandemic monitoring and management

“…Abid et al 41 propose a blockchain-enabled framework, named, NovidChain for COVID-19 test/vaccination certificates to ensure data integrity and immutability. Ghosh, and Mukherjee 42,43 present cloud-fog-edge enabled framework named STROVE to provision fast healthcare services leveraging femtolet and mobility-based solutions. Mohan et al 44 proposed a hybrid model for forecasting impact of COVID-19 in long-term both in India and global level.…”

Energy and Latency Optimization in Edge-Fog-Cloud Computing for the Internet of Medical Things

“…During COVID-19, which imposed a greater emphasis on the use of remote health monitoring tools (e.g., smart hospitals and home-based health monitoring services), the adoption of IoMTenabled healthcare became a more widespread practice to enhance efficiency and productivity during the pandemic [3]. Experts are now developing adaptable systems based on Machine-to-Machine (M2M) interactions thanks to the usage of these IoMT sensors, saving time for patients and medical staff, and facilitating patient care at home [4].…”

“…The processing of vast amounts of data can be done more effectively to assist big data analytics by using cloud services. Through the cloud, IoT subsystems do not have to deal with extensive computing, which will increase the battery lifetime of these devices [3]. The cloud-based framework's main shortcomings include network connections, the delay in getting the results, and even security concerns.…”