IoT-Enabled Alcohol Detection System for Road Transportation Safety in Smart City

In this paper, an alcohol detection system was developed for road transportation safety in smart city using Internet of Things (IoT) technology. Two Blood Alcohol Content (BAC) thresholds are set and monitored with the use of a microcontroller. When the first threshold is reached, the developed system transmits the BAC level of the driver and the position coordinates of the vehicle to the central monitoring unit. At the reach of the second BAC threshold, the IoT-enabled alcohol detection system shuts down the vehicle’s engine, triggers an alarm and puts on the warning light indicator. A prototype of this scenario is designed and implemented such that a Direct Current (DC) motor acted as the vehicle’s engine while a push button served as its ignition system. The efficiency of this system is tested to ensure proper functionality. The deployment of this system will help in reducing the incidence of drunk driving related road accidents in smart cities

A Systematic Evaluation of Literature on Internet of Things (IoT) and Smart Technologies with Multiple Dimensions

The advent of state of the art advanced technologies is necessitated by the ever-increasing onset and infiltration of our lives by the smart devices and gadgets for providing an array of services. The conventional methods and techniques already becoming obsolete and the consistent and persistent demand for provision of high end services with a greater degree of accuracy by various sectors, paves the way for collaboration of smart technologies such as Internet of things, Internet of everything, Internet of Vehicles etc. with the smart gadgets and devices. This systematic review tries to explore the avenues for research and multiple streaming of segments by the analysis of allied smart systems comprising of smart devices and multi-dimensional IoT, IoE, IoV etc.&nbsp

Helmet-Mounted Display System Based on IoT

Many people enjoy motorcycle riding and there are thousands of people who have lost their lives due to road accidents. This is mainly due to the delay in the state of emergency that must be provided to the victims. The helmet-mounted display system that uses the Internet of Things (IoT) reduces accidents and informs its contacts in emergencies so the helmet module contains sensors to determine the passenger\u27s pulse rate, alcohol content, and vibration intensity. The pulse rate sensor is used to determine whether the rider has worn the helmet and which will be connected to the rider\u27s start of his trip on the road. That\u27s why we implemented a prototype proposal using the IoT to connect all devices and make it easier for the user to reduce road accidents by displaying all their needs in full on the helmet screen. So, in the implementation of our proposal, we made several systems connected with Raspberry Pi 4 which are Global Positioning System (GPS) applications, camera systems, and sensors that display all output data in the background, after that will transmit all these data from Raspberry Pi 4 to Raspberry Pi 3 through User Datagram Protocol (UDP), which Raspberry Pi 3 connected with Digital Light Processing )DLP) projector to display all background data as a hologram to the user giving him safety on the road without any distractions

IoT-Based Vehicle Monitoring and Driver Assistance System Framework for Safety and Smart Fleet Management

Curbing road accidents has always been one of the utmost priorities in every country. In Malaysia, Traffic Investigation and Enforcement Department reported that Malaysia’s total number of road accidents has increased from 373,071 to 533,875 in the last decade. One of the significant causes of road accidents is driver’s behaviours. However, drivers’ behaviour was challenging to regulate by the enforcement team or fleet operators, especially heavy vehicles. We proposed adopting the Internet of Things (IoT) and its’ emerging technologies to monitor and alert driver’s behavioural and driving patterns in reducing road accidents. In this work, we proposed a lane tracking and iris detection algorithm to monitor and alert the driver’s behaviour when the vehicle sways away from the lane and the driver feeling drowsy, respectively. We implemented electronic devices such as cameras, a global positioning system module, a global system communication module, and a microcontroller as an intelligent transportation system in the vehicle. We implemented face recognition for person identification using the same in-vehicle camera and recorded the working duration for authentication and operation health monitoring, respectively. With the GPS module, we monitored and alerted against permissible vehicle’s speed accordingly. We integrated IoT on the system for the fleet centre to monitor and alert the driver’s behavioural activities in real-time through the user access portal. We validated it successfully on Malaysian roads.  The outcome of this pilot project benefits the safety of drivers, public road users, and passengers. The impact of this framework leads to a new regulation by the government agencies towards merit and demerit system, real-time fleet monitoring of intelligent transportation systems, and socio-economy such as cheaper health premiums. The big data can be used to predict the driver’s behavioural in the future

IoT-Based Vehicle Monitoring and Driver Assistance System Framework for Safety and Smart Fleet Management

Curbing road accidents has always been one of the utmost priorities in every country. In Malaysia, Traffic Investigation and Enforcement Department reported that Malaysia’s total number of road accidents has increased from 373,071 to 533,875 in the last decade. One of the significant causes of road accidents is driver’s behaviours. However, drivers’ behaviour was challenging to regulate by the enforcement team or fleet operators, especially heavy vehicles. We proposed adopting the Internet of Things (IoT) and its’ emerging technologies to monitor and alert driver’s behavioural and driving patterns in reducing road accidents. In this work, we proposed a lane tracking and iris detection algorithm to monitor and alert the driver’s behaviour when the vehicle sways away from the lane and the driver feeling drowsy, respectively. We implemented electronic devices such as cameras, a global positioning system module, a global system communication module, and a microcontroller as an intelligent transportation system in the vehicle. We implemented face recognition for person identification using the same in-vehicle camera and recorded the working duration for authentication and operation health monitoring, respectively. With the GPS module, we monitored and alerted against permissible vehicle’s speed accordingly. We integrated IoT on the system for the fleet centre to monitor and alert the driver’s behavioural activities in real-time through the user access portal. We validated it successfully on Malaysian roads.  The outcome of this pilot project benefits the safety of drivers, public road users, and passengers. The impact of this framework leads to a new regulation by the government agencies towards merit and demerit system, real-time fleet monitoring of intelligent transportation systems, and socio-economy such as cheaper health premiums. The big data can be used to predict the driver’s behavioural in the future

Analytical Study of an IOT-based Accident Detection and Information Management System

Accidents wreak havoc on victims, costing them valuable time and money. After thorough investigation, it has been shown that the majority of accidents result in fatalities as a result of poor communication with the relevant medical authorities and the ensuing dearth of prompt medical attention. Several sensor nodes are combined in a single system to forecast likely accident combinations. Lab view-based simulation was used to handlepossible conditions for an accident to happen. With the IoT Interface, theproposed design would enable a novel model in the vehicular communication system to recognize various accident situations and provide associated information to the needy. The proposed model would handle all potential combinations and comparative analyses from low to high end cars, as well as provide a strategy framework for future IoT enabled v2v communication networks

A Recent Connected Vehicle - IoT Automotive Application Based on Communication Technology

Realizing the full potential of vehicle communications depends in large part on the infrastructure of vehicular networks. As more cars are connected to the Internet and one another, new technological advancements are being driven by a multidisciplinary approach. As transportation networks become more complicated, academic, and automotive researchers collaborate to offer their thoughts and answers. They also imagine various applications to enhance mobility and the driving experience. Due to the requirement for low latency, faster throughput, and increased reliability, wireless access technologies and an appropriate (potentially dedicated) infrastructure present substantial hurdles to communication systems. This article provides a comprehensive overview of the wireless access technologies, deployment, and connected car infrastructures that enable vehicular connectivity. The challenges, issues, services, and maintenance of connected vehicles that rely on infrastructure-based vehicular communications are also identified in this paper

Real-time monitoring system for drunk driver through Internet of Things - a case of Nairobi County, Kenya

Thesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore UniversityOne of the major causes of traffic accidents and crashes globally is drunk driving. Though driving under influence of alcohol is illegal, drivers still find themselves doing it. This has resulted to deaths and fatalities which affect the economy negatively. Currently, different technologies have been adopted to reduce the vice without success. In Kenya, breathalyzers are being used by traffic police to monitor drunk drivers. This technology has failed due to corruption. The reason being the culprits are able to buy their way out. Technological innovation needs to be implemented in a cost effective, efficient and legal manner. This enables to combat drunken driving on the roads easily. The researcher applies the V-Model Methodology to design, implement and test of a realtime monitoring system for drunk driver through IoT. The system uses fuzzy logic based algorithm to analyze the response of MQ-3 and MQ-135 sensors. Sensor fusion is achieved through processing the analog to digital converted values of the sensor output using an algorithm to determine alcohol concentration in the breath (BAC). The analyzed result determines whether the Blood alcohol concentration (BAC) is within the legally permissible standards. Upon the detection of such a situation, an alarm is activated. Additionally, an ‘alert SMS’ indicating the drunk driver’s location as tracked by the GPS receiver on the same system and the vehicle registration number is communicated to the SACCO managers using GSM cellular network to take appropriate action of intercepting the vehicle. The tested real-time results indicated the successful implementation of the system

A profile-driven dynamic risk assessment framework for connected and autonomous vehicles

The Internet of Things has already demonstrated clear benefits when applied in many areas. In connected and autonomous vehicles (CAV), IoT data can help the autonomous systems make better decisions for safer and more secure transportation. For example, different IoT data sources can extend CAV's risk awareness, while the incoming data can update these risks in real-time for faster reactions that may mitigate possible damages. However, the current state of the art CAV research has not addressed this matter well enough. This paper proposes a profile-driven approach to manage IoT data in the context of CAV systems through a dynamic risk management framework. Unlike the current inflexible risk assessment strategies, the framework encourages more flexible investigation of risks through different risk profiles, each representing risk knowledge through a set of risk input considerations, assessment methods and optimal reaction strategies. As the risks change frequently with time and location, there will be no single profile that can cover all the risks that CAVs face on the road. The uses of different risk profiles, therefore can help interested parties to better understand the risks and adapt to various situations appropriately. Our framework includes the effective management of IoT data sources to enable the run-time risk assessment. We also describe a case study of using the proposed framework to manage the risks for the POD being developed in the Innovate UK-funded CAPRI project