An algorithm for IoT based vehicle verification system using RFID

The verification of vehicle documents is an important role of transport department which is rising day by day due to the mass registration of the vehicles. An automated vehicle verification system can improve the efficiency of this process.  In this paper, we propose an IOT based vehicle verification system using RFID technology. As a result, the vehicle checking which is done now manually can be replaced by automation. There is a loss of a significant amount of time when the normal vehicle checking is done manually. The proposed system will make this process automated. The present verification process is using inductive loops that are placed in a roadbed for detecting vehicles as they pass through the loop of the magnetic field. Similarly, the sensing devices spread along the road can detect passing vehicles through the Bluetooth mechanism. The fixed audio detection devices that can be used to identify the type of vehicles on the road. Other measurements are fixed cameras installed in specific points of roads for categorising the vehicles. But all these mechanisms cannot verify the documents and certificates of the vehicles. In our work, we have suggested an algorithm using RFID technology to automate the documentation verification process of the vehicles like Pollution, Insurance, Rc book etc with the help of RFID reader placed at road checking areas. This documents will be updated by the motor vehicle department at specific periods

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Proof of Travel for Trust-Based Data Validation in V2I Communication Part I: Methodology

Previous work on misbehavior detection and trust management for Vehicle-to-Everything (V2X) communication can identify falsified and malicious messages, enabling witness vehicles to report observations about high-criticality traffic events. However, there may not exist enough "benign" vehicles with V2X connectivity or vehicle owners who are willing to opt-in in the early stages of connected-vehicle deployment. In this paper, we propose a security protocol for the communication between vehicles and infrastructure, titled Proof-of-Travel (POT), to answer the research question: How can we transform the power of cryptography techniques embedded within the protocol into social and economic mechanisms to simultaneously incentivize Vehicle-to-Infrastructure (V2I) data sharing activities and validate the data? The key idea is to determine the reputation of and the contribution made by a vehicle based on its distance traveled and the information it shared through V2I channels. In particular, the total vehicle miles traveled for a vehicle must be testified by digital signatures signed by each infrastructure component along the path of its movement. While building a chain of proofs of spatial movement creates burdens for malicious vehicles, acquiring proofs does not result in extra cost for normal vehicles, which naturally want to move from the origin to the destination. The proof of travel for a vehicle can then be used to determine the contribution and reward by its altruistic behaviors. We propose short-term and long-term incentive designs based on the POT protocol and evaluate their security and performance through theoretical analysis and simulations

E-Wild Life Alert: Tackling the Human-Wildlife Conflict Problem

Depletion of resources meant for both human and animal survival leads to competition for these. Human-wildlife conflict (HWC) occurs when these two parties compete for resources such as space, water, and food. If not properly managed, HWC can lead to loss of livelihoods and even loss of life. This paper discusses the design and development of an E-Wildlife Alert application that uses machine learning to detect dangerous animals. Using the Design Science Research method, a convolutional neural network is trained to build an artifact that detects five dangerous animals from an African context. The artifact is mounted on a robot that propels it around, providing a 360 degree turn for the image capturing camera to get a full view of the environment. On detecting any object in the way, the robot turns to avoid the obstacle. The E-Wild Life Alert application is able to detect five dangerous animals with an accuracy of up to 98%. On detecting any such animal in the vicinity, the application sends an SMS to a phone number in the system, logged as wildlife parks officer. This system would be useful, first to humans bordering areas with dangerous animals, as it protects them from these. Secondly, the tourism industry can benefit from the application as it reduces the number of wildlife killed on straying. In the long run, such an application is beneficial to nature in terms of conservation, promoting species diversity

Electric Vehicle - Smart Grid Integration: Load Modeling, Scheduling, and Cyber Security

The modern world has witnessed the surge of electric vehicles (EVs) driven by government policy worldwide to reduce transportation’s dependence on fossil fuels. According to (Slowik, 2019), the global EV market has grown sharply with the annual light-duty EV sales surpassing 2 million in 2018, which is about a 70% increase from 2017. The increase in EV population implies the rise in energy demand, and that introduces new challenges to the electricity sector. EV charging load demand in high penetration scenarios, which is foreseen, may lead to stability and quality issues in power grids. Generation capacity and the electricity infrastructure upgrade may be required to address those issues; however, it increases generation costs significantly. The most common EV chargers installed today deliver around 7 kW of power, which is over four times that of an average household power consumption in the US. EV charging load often shows two peaks in a day, one in the morning when people plug in the EV at the workplace and the other in the evening when people get home from work. Without proper energy management for EV charging, the vast power demand due to a large number of plugged-in EVs can stress the electric grid, degrade the electric power quality, and impact the wholesale electricity market. Although an EV battery may store energy up to 80 kWh, which requires more than 10 hours to charge at 7kW from empty, we found that most EVs need only 12 kWh per charge or 1.7 hours at 7 kW to meet daily commute requirement while they stay in the parking garage for a more extended period. This implies that EVs can have considerable time-flexibility for charging, and it is not necessary to start chargingright after plugging in, which is likely to result in the charging power add-up. A proper EV charging schedule can well allocate the charging load to prevent power peaks. Therefore, EV charging scheduling can play a significant role in mitigating the adverse effects of vast EV charging demand without upgrading the power grid capacity.To optimize the EV charging schedule while satisfies EVs’ charging demand, each EV’s stay duration and energy need are essential parameters for the optimization. Those parameters are based on predictions to minimize human intervention. Nonetheless, the uncertainty of EV user behavior poses a challenge to the prediction accuracy. Therefore, this dissertation demonstrates an ensemble machine learning-based method to model and predict the EV loads accurately, thereby improving the performance of EV charging scheduling.On the other hand, this smart EV-grid integration, which requires massive communication, including collecting, transmitting, and distributing real-time data within the network, makes it more susceptible to cyber-physical threats. Potential breaches could not only affect grid operation but also reduce consumers’ willingness to adopting EVs over conventional fuel-powered vehicles. This dissertation also presents the vulnerability analysis and risk assessment for a smart EV charging system to develop the countermeasures to secure the network. Also, while it is inevitable that the security has flaws, this dissertation provides a novel anomaly detection approach based on the invariant correlations of different measurements within the EV charging network

A Review Paper on Accident Detection System Using Intelligent Algorithm for VANET

Our lives became easier with the Quick accretion of technology and infrastructure. The advent of technology has also rise the traffic hazards and the road accident take place repeatedly which causes massive loss of life and property because of the poor emergency facilities. Recently, intelligent transportation systems (ITS) have emerged as an efficient way of improving interpretation of transportation systems and enhancing travel safety. Accident detection systems are one of the most effective (ITS) tools. The accident detected system which based on Global Positioning System (GPS) and Global System for Mobile communication (GSM) can be accomplish though one or several sensors, the system can gathers the information and coordinates of accident spot then send this data to the rescues services center over a network link in shortest time, It represented as an instance helping system. In this review paper, we proposed an intelligent system that composed of a GPS receiver, Vibration sensor, GSM Modem and integrated with Vehicular AD-Hoc Network (VANET). The employ of (VANET) by enhanced Ad hoc On-Demand Distance Vector protocol (AODV) helps these services in finding the optimum route to the emergency message. The use of GSM, GPS, and VANET technologies allows the system to track vehicle and provides the most instant and accurate information about the vehicle accident spot. Keywords: GPS, GSM, VANET, AODV