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The spectrum of deployed wireless cellular communication systems is found to be under-utilized, even though licensed spectrum is at a premium. To efficiently utilize the bandwidth left unused in a cellular system, which we denote as the primary system (PRI), we design a system with an ad hoc overlay network, which we denote as the secondary system (SEC). The basic design principle is that the SEC operates in a nonintrusive manner and does not interact with the PRI. We develop the AS-MAC, an Ad hoc SEC Medium Access Control protocol to enable the interoperation of the PRI-SEC system. We address a number of technical challenges pertinent to this networking environment, and evaluate AS-MAC. Our performance evaluation results show that, in a single-hop ASN, the AS-MAC transparently utilizes 75% of the bandwidth left unused by the PRI, while, in multi-hop ASNs, due to spatial reuse, the AS-MAC can utilize up to 180% of the idle PRI resources.

A Bandwidth Sharing Approach to Improve Licensed Spectrum Utilization

Regular hospital visits can be expensive, particularly in rural areas, due to travel costs. In the era of the Covid-19 Pandemic, where physical interaction becomes risky, people prefer telemedicine. Fortunately, medical visits can be reduced when telemedicine services are used through video conferencing or other virtual technologies. Thus, telemedicine saves both the patient's and the health care provider time and the cost of the treatment. Furthermore, due to its fast and advantageous characteristics, it can streamline the workflow of hospitals and clinics. This disruptive technology would make it easier to monitor discharged patients and manage their recovery. As a result, it is sufficient to state that telemedicine can create a win-win situation. This paper aims to explore the significant capabilities, features with treatment workflow, and barriers to the adoption of telemedicine in Healthcare. The paper identifies seventeen significant applications of telemedicine in Healthcare. Telemedicine is described as a medical practitioner to diagnose and treat patients in a remote area. Using health apps for scheduled follow-up visits makes doctors and patients more effective and improves the probability of follow-up, reducing missing appointments and optimising patient outcomes. Patients should have an accurate medical history and show the doctor any prominent rashes, bruises, or other signs that need attention through the excellent quality audio-video system. Further, practitioners need file management and a payment gateway system. Telemedicine technologies allow patients and doctors both to review the treatment process. However, this technology supplements physical consultation and is in no way a substitute for a physical consultation. Today this technology is a safe choice for patients who cannot go to the doctor or sit at home, especially during a pandemic.

Telemedicine for healthcare: Capabilities, features, barriers, and applications.

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In the era of the Internet of Things (IoT) and Industry 4.0, the indoor usage of smart devices is expected to increase, thereby making their location information more important. Based on various practical issues related to large delays, high design cost, and limited performance, conventional localization techniques are not practical for indoor IoT applications. In recent years, many researchers have proposed a wide range of machine learning (ML)-based indoor localization approaches using Wi-Fi received signal strength indicator (RSSI) fingerprints. This survey attempts to provide a summarized investigation of ML-based Wi-Fi RSSI fingerprinting schemes, including data preprocessing, data augmentation, ML prediction models for indoor localization, and postprocessing in ML, and compare their performance. Any ML-based study is heavily reliant on datasets. Therefore, we dedicate a significant portion of this survey to the discussion of dataset collection and open-source datasets. To provide good direction for future research, we discuss the current challenges and potential solutions related to ML-based indoor localization systems.

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Machine Learning Based Indoor Localization Using Wi-Fi RSSI Fingerprints: An Overview

Advancement in wireless technologies to improve telemedicine is one of the major goals in recent times. Wireless telemedicine for emergency primary healthcare is a technology which provides mobile healthcare and exchange of medical data from ambulances or rural healthcare centers to hospitals. This helps the hospitals to understand patients' medical condition before they arrive. The idea is to be prepared in advance for hospitals to respond to such cases. This work focuses on creating a vehicular ad hoc network scenario for telemedicine, where an attempt is made to identify an optimal solution using 802.11 networking standard. A vehicle-to-vehicle connection is created which has been evaluated using various node densities by choosing 802.11n, 802.11p and 802.11b with AODV (Ad-Hoc On demand Distance Vector) routing protocol. Constant bit-rate traffic is used between the ambulance and hospital. Validations for the standards are carried out for the parameters PLR (Packet Loss Ratio), delay and throughput considering blood pressure, video and audio transmission. The performance results are analyzed for all three standards based on mobility and varying vehicular speeds. We have compared the results of various parameters for each scenario and attempted to identify the better performing standard. NS3 has been used for simulation in networks, whereas for traffic simulation SUMO (Simulation of Urban Mobility) is used.

Feasibility and performance evaluation of VANET techniques to enhance real-time emergency healthcare services

Telemedicine systems are becoming prevalent in today's healthcare scenarios, especially in India where a large portion of the population resides in remote and rural regions where availability of specialty healthcare is scant. Many such telemedicine system implementations can be found in the existing literature. Since critical data are being transmitted over these networks, the reliability of these systems is highly important. This paper discusses about the quality of service (QoS) requirements for achieving reliability for such systems. The paper discusses the importance and acceptance of such rescue vehicles which are equipped with the telemedicine facilities. This involves the role of paramedic assistance, multiple access technologies along with acquisition and remission of vital parameters such as electrocardiogram (ECG), blood pressure (BP), pulse rate (PR) etc. to a specialist doctor at the remote hospital. A comprehensive survey has been done among the various stakeholders of the proposed system. The paper focuses on the need for the QoS mechanisms in the proposed telemedicine system for the rural rescue and health care emergencies.

QoS based telemedicine technologies for rural healthcare emergencies

A network testbed is a testing environment which facilitates to check the interaction between simulations and the real nodes. As it is very difficult to incorporate all the hardware resources required into the project, it is a model to make the simulated network interact with the real nodes. Network testing can be carried out by using simulators and emulators but the performance of these models are not enough. So the comparative study was carried out and found that simulators and emulators lack in giving the results that are not accurate when compared to real network. Therefore, an approach has been proposed where the simulator and emulator combination is formed and this gives us a new way to deal with large scale testing environment. This study helps researchers to choose appropriate combination of network simulator and hypervisor to construct an emulation platform for a network testbed.

Technologies for Network Testing: A Hybrid Approach

When deploying localization techniques using wireless devices with only less amount of system resources, indoor WiFi localization is a difficult task. GPS (Global Positioning System) can provide a fairly accurate position of the user, but it is usually not used indoors because of the degradation of signals due to the structure of the building. Due to the unsteady nature of Received Signal Strength Indicator (RSSI), accurate results are hard to generate, in spite of the usage of various alternative WiFi localization techniques. We have attempted to improve the accuracy of localizing the user by implementing wall detection and pixel calculation to trilateration technique in smartphones. The users having WiFi enabled devices like a smartphone can locate their position and request for help in case of emergency with the implementation of WiFi localization on mobile devices. This study proves that the selection of access points used for generating the position of the user substantially affects the accuracy.

TELIL: A Trilateration and Edge Learning based Indoor Localization Technique for Emergency Scenarios

A network testbed is a testing environment which facilitates to check the accuracy and the performance of a newly designed network. Network testing can be carried out by using simulators and emulators but the performance of these models is not enough. So, a comparative study was carried out and found that simulators and emulators lack in giving the results that are not accurate when compared to real networks. Therefore, several network testbed combinations comprising of real nodes, simulated nodes and virtual nodes have been proposed. These include network testbed using real systems which comprises of only real nodes, network testbed using xen hypervisor which comprises of a combination of three types of nodes, network testbed using VirtualBox which comprises of two types of nodes and network testbed using simulation which comprises of only simulated nodes are proposed in order to ease the selection of the best network testing methodology based on the scenario and the scale of the newly designed network.

Adwitiya Mukhopadhyay

Papers

Feasibility and performance evaluation of VANET techniques to enhance real-time emergency healthcare services

QoS based telemedicine technologies for rural healthcare emergencies

Technologies for Network Testing: A Hybrid Approach

TELIL: A Trilateration and Edge Learning based Indoor Localization Technique for Emergency Scenarios

Network Performance Testing: A Multi Scenario Contemplate