## 2 Literature Review  
During the years 2020 and 2021, more than 1 million humans across the world were infected with the COVID-19 virus [9]. This exponential increase in the disease spread led to a surge in global demand for intensive care unit (ICU) wards. In order to reduce the strain on already overburdened hospitals, adopting telemedicine would be great help. Based on a study performed in England, [PERSON] et al. provide a model for a telemedicine scenario [10]. The paper highlights how the healthcare infrastructure in England mitigated the morbidity rate in the country during the COVID-19 pandemic. In contrast, in most developing countries, due to a lack of enough healthcare access in rural communities, COVID-19 patients need to be transported by ambulances to urban locations to receive the required healthcare support [11; 12]. This introduces the new challenge of monitoring the patients while they are transported in mobile ambulances. During the transit of COVID-19 patients, dynamic monitoring of their vital parameters is important. It is also important that the patient's risk levels be monitored continuously, as the healthcare dissemination plan might change according to the varying risk levels. The existing literature [13; 14; 15] details multiple scoring systems for determining the critical level of a patient. During emergencies, the lack of a common standard leads to ambiguity and misunderstandings in information exchange during inter-hospital transfers. However, existing scoring mechanisms consider pathological parameters that would be challenging to measure in a moving ambulance and would require a dedicated laboratory setup available only in hospitals. In order to enable the ambulance operator and doctors to categorize the patient easily and facilitate the healthcare practitioners to function smoothly, we have proposed our monitoring algorithm WDMA-Edge and scoring mechanism OFEHS. In order to keep the doctor informed about the patient's vital signs and the risk level, this information needs to be transmitted to the remote hospital during the transit of the ambulance. Insufficient network access in rural areas, which is as little as 18%, is observed as one of the major challenges in data dissemination [16; 17; 18]. The authors of [19] showcase vehicular-based network access using the 802.11p standard and the authors of [20] present a health monitoring system utilizing heterogeneous communication based on 6 LoWPAN and the cellular network. However, both the solutions lack seamless continuous connectivity. The degradation of the signal strength of communication technologies during high-speed traversal of mobile vehicles poses another major challenge to mobile telemedicine services [21; 22]. Storing the data in a telemedicine scenario yields several concerns with respect to the interoperability and privacy of healthcare devices and data while using cloud-based technologies [23]. Therefore, most of the existing solutions are not acceptable for solving the specific requirements for mobile telemedicine solutions and are also very expensive, leading to non-affordability for wide deployments in mobile ambulances. Achieving stringent QoS requirements for seamless data transmission from mobile ambulances under different traffic scenarios is considered another challenge. The existing studies do not detail the impacts due to each and every factor such as varying vehicular density and velocity along with spatio-temporal variations, and do not propose an integrated solution for meeting the stringent QoS requirement [24; 25; 26; 27; 28]. This paper addresses the lacuna by proposing novel algorithms and methods such as IITA and ITSF. Multiple architectures for telemedicine can be found in the existing literature. For instance, [PERSON]. [29] presents an IoT-based architecture which can have remote access to a patient's vital signs, such as heartbeat and BP. The measured vital signs are further transmitted over the communication network to a doctor's mobile phone.