With the improvement in transportation infrastructure and in-vehicle technology in addition to a meteoric increase in the total number of commercial and non-commercial vehicles on the road, traffic accidents may occur, which usually cause a high death toll. More than half of these deaths occur due to a delayed response by medical care providers and rescue authorities. The chances of survival of an accident victim could increase drastically if immediate medical assistance is provided at an accident location. This work proposes a low-cost accident detection and notification system, which utilizes a multi-tier IoT-based vehicular environment; principally, it uses V2X Communication and Edge/Cloud computing. In this work, vehicles are equipped with an On-Board Unit (OBU) in addition to mechanical sensors (accelerometer, gyroscope) for reliable accident detection along with a Global Positioning System (GPS) module for identification of accident location. In addition to this, a camera module is implanted on the vehicle to capture the moment when an accident takes place. In order to facilitate inter-vehicle communication (IVC), OBU in each vehicle incorporates a wireless networking interface. Once an accident occurs, a vehicle detects it and generates an alert message. It then sends the message along with the accident location to an intermediate device, placed at the edge of the vehicular network, and therefore called an edge device. Upon receiving the notification, this edge device finds the nearest hospital and makes a request for an ambulance to be dispatched immediately. It also performs some preprocessing of data and effectively acts as a bridge between the sensors installed inside the vehicle and the distant server deployed in the cloud. A significant issue that the traffic authorities are currently facing is the real-time visualization of data obtained through such environments. Wireless interfaces are usually capable of forwarding real-time sensor data; however, this feature is not yet commercially available in the OBU of the vehicle; therefore, practical implementation is carried out using the Internet of things (IoT) in order to create a network among the vehicles, the edge node, and the central server. By performing analysis on the adequate acquired data of road accidents, the constructive plans of action can be devised that may limit the death toll. In order to assist the relevant authorities in performing wholesome analysis of refined and reliable data, a dynamic front-end visualization is proposed, which is hosted in the cloud. The generated charts and graphs help the personnel at relevant organizations to make appropriate decisions based on the conclusive analysis of processed and stored data.

The increase in the population of cities and the number of vehicles leads to increase in congestion on roads and accidents. The lack of quick medical service on road accidents is the major cause of death. In such situation, an automatic accident detection can help to save the loss of life. In this paper, a prototype is designed for an automatic accident detection using Vehicular Adhoc Network (VANET) and Internet of Things (IoT). The application is able to detect accident and severity of the emergency level with the help of mechanical and medical sensors deployed in the vehicle. In case of emergency, the message is sent to a hospital using VANET, where our central server is able to find out the location of the accident and nearest medical center. It sends a message for an ambulance after detecting basic information. In order to clear the path on the way to accident's location, the client application on the ambulance generates alert messages.

WAVE by IEEE, CALM by ISO and Car-to-Car are the popular VANET architectures. These architectures mainly focus on safety applications. IEEE 802.11p is the IEEE recommended MAC and PHY layer standard for VANET. Different VANET pro- tocol stacks recommend this standard not only for the safety applications but also other applications. In this paper, we focus on Multimedia-based ad-hoc networking and WLAN aspects for VANETs. The use of Multimedia applications is increasing day by day. Applications like Voice over IP (VoIP), video conferencing, online gaming and file transfer etc. demand time bounded and high throughput services. To fulfill these demands in a vehicular environment, there is a need to evaluate the current IEEE VANET standard for MAC (IEEE 802.11p) to know its limitations for these applications and move towards exploration of a new standard. IEEE 802.11n claims high throughput up to 300Mbps and proved to be more suitable standard for multimedia applications. In this paper, we have evaluated IEEE 802.11p and IEEE 802.11n specifically for multimedia applications in VANET. Simulation results show, IEEE 802.11n comparatively performs better for multimedia applications in urban environment in low BER (bit error rate) as well as high BER as compared to IEEE 802.11p

Background: Coronavirus disease 2019 devastated lives in care homes for older people, where residents faced higher mortality risks than the general population. Infection prevention and control decisions were critical to protect these vulnerable residents. Infection prevention and control measures like ‘lockdowns’ had their own risks, such as social isolation, alongside assumed benefits. A key non-pharmaceutical intervention for managing infections is contact tracing. Traditional contact tracing, which relies on recalling contacts, is not feasible in care homes where approximately 70% of residents have cognitive impairments. The CONtact TrAcing in Care homes using digital Technology intervention introduces Bluetooth-enabled wearable devices for automated contact tracing. We provided structured reports (scheduled regularly and in reaction to positive COVID-19 cases) on contact patterns to homes to support better-informed infection prevention and control decisions and potentially reduce blanket restrictive measures. We also partnered with the PROTECT COVID-19 research team to examine air quality in two of our homes. Methods: CONTACT was a non-randomised mixed-method feasibility study in four English care homes. Recruitment was via care home research networks, with individual consent. Data collection included routine device data, case report forms, qualitative interviews, field observations of care home activity and an adapted Normalisation Measure Development questionnaire survey to explore implementation using normalisation process theory. Quantitative data were analysed using descriptive statistical methods, and qualitative data were thematically analysed using normalisation process theory. Intervention and study delivery were evaluated against predefined progression criteria. Results: Of 156 eligible residents, 105 agreed to wear a device, with 102 (97%) starting the intervention. Of 225 eligible staff, 82.4% (n = 178) participated. Over 2 months, device loss and battery failure were significant: residents lost 11% of devices, with half replaced. Staff lost fewer devices, just 6.5%, but < 10% were replaced. Fob wearables needed more battery changes than card-type devices (15% vs. 0%). Homes variably understood structured and reactive feedback but were unlikely to act on it. Researcher support for interpreting reports was valued. Homes found information useful when it confirmed rather than challenged preconceived contact patterns. Staff privacy concerns were a barrier to adoption. Study procedures added to existing work, making participation burdensome. The perceived burden of participation, amplified by the pandemic context, outweighed the benefits. CONTACT did not meet its quantitative or qualitative progression criteria. Limitations: Researchers had to pragmatically adapt procedures, resulting in suboptimal implementation choices from an implementation science perspective. Future research should co-design interventions with homes, focusing on implementation and wearability as much as technical effectiveness. Conclusion: A definitive trial of CONTACT was not feasible or acceptable to care homes, partly due to the shifting pandemic context and demands on homes. With more effective implementation, Bluetooth-enabled wearable systems as part of ‘Internet of Things’ in homes could be used to: (1) better understand airborne transmission risks, ventilation and air quality and (2) make important relational aspects of care quality and residents’ quality of life more transparent. Future work: We will continue to explore the possibilities of Bluetooth-enabled wearables for modelling social networks, movement, infection risks and quality in care homes with academic and care partners. Funding: This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number NIHR132197.