Car Theft Research Articles

XAI-SALPAD: Explainable deep learning techniques for Saudi Arabia license plate automatic detection

In recent decades, automatic license plate recognition (ALPR) has emerged as a critical application of artificial intelligence in intelligent transportation systems (ITS), addressing a multitude of existing issues. Several algorithms have been developed to improve ALPR accuracy under a variety of conditions, each with its own set of strengths and limitations. The KSA intends to digitize traditional services as part of its Vision 2030 initiative. In this methodology, the ALPR system for accurately recognizing KSA's license plates (LP) leverages deep neural networks (DNNs) as a powerful technique, capable of performing effectively in unconstrained environments with images taken under various conditions, even when the training data is limited. The approach employs YOLOv8 to detect LPs and alphanumeric characters in real-time, followed by using a convolutional neural network (CNN) for character recognition. According to our finding, the YOLOv8 model outperforms other models in the identification of LPs, achieving remarkable accuracy and F1 scores (mAP@0.5 = 0.96 and mAP@0.95 = 0.97). As a result, YOLOv8 was chosen for SLP character recognition. This strategy is appropriate for ITS since it tackles a number of issues, like decreasing car theft and improving public safety. Furthermore, a locally interpretable agnostic model (LIME) offers justifications that help users better understand the model. The system's provision of clear explanations for its decisions not only satisfies performance standards but also corresponds with the increasing need for explainable AI, guaranteeing an efficient and responsible implementation.

Juridical Review of the Criminal Act of Car Theft by Rental Car Mode According to the Criminal Law (KUHP)

Juridical Review of the Criminal Act of Car Theft by Rental Car Mode According to the Criminal Law (KUHP)

Joyriding Among Young First Nations Australians: Assessing Police Trust and Confidence Through the Lens of Youth and Key Stakeholders

Young First Nations Australians typically distrust and are reluctant to cooperate with the police. This article discusses data from a pilot intervention programme regarding First Nations young people’s involvement in car theft and joyriding. We conducted seven in-depth interviews with young Australians – most of whom identified as First Nations Australians – and six key community stakeholders who helped to deliver the programme. Our findings indicate that both sample groups held negative and distrusting perceptions of the police which, for the young people, were often precipitated by perceived discriminatory and procedurally unjust encounters with the police. We argue that heavy-handed and discriminatory policing of young First Nations Australians may perpetuate youth offending and joyriding behaviours among this group. The article argues that the police should adopt more community-oriented policing approaches to build trust with young First Nations Australians.

A preliminary study to identify critical factors for evaluating the effect of car-lock sounds on drivers

Car-lock sounds are designed to inform the lock status of vehicles. However, drivers often experience a lack of confidence regarding whether the car is locked, and car thefts persistently occur, frequently attributed to unlocked doors. Without identification of critical factors for evaluating effects of car-lock sounds on drivers, a strategy to car-lock sound design with increased locking efficiency remains implicit. This study proposes a method to identify critical factors influencing drivers’ perceived certainty of car-lock status and behaviours during car-locking. An experiment was conducted to simulate the locking process and verbal protocol analysis was employed to comprehend participants’ cognitive processes and behaviours. The results show that mechanical sound yielded high certainty and few hesitations, while tonal and crisp sound elicited low certainty and frequent hesitations. Seven critical factors on participants’ behaviours and cognitive processes were identified, which provides a data-driven approach for future research in car-lock sounds evaluation and design.

Eight Focus Crimes in Baguio City During the Post-Covid 19: A Situationer

The study evaluated the crime trends during the post-COVID-19 pandemic, specifically the eight focused crimes identified by the law enforcers in Baguio City. It aimed to assess the changes in the occurrence and frequency of the eight focus crimes and identify the key factors contributing to any shifts in the patterns of these focus crimes during the post-pandemic period. A total of 17 police investigators participated in the study and were selected through purposive sampling. The Eight Focus Crimes include; Murder, Homicide, Physical Injury, Rape, Theft, Robbery, Car theft, and Motorcycle Theft wherein Physical Injuries, Theft, and Robbery were the most reported incidents. The study used documentary analysis and semi-structured interviews to analyze the gathered data. Based on the findings, the key factors that contributed to the shifts in the patterns of these focus crimes during the post-pandemic period were movement and travel restrictions, economic restraints, and the impact of technological advancement.

Individual-level social determinants of health and allostatic load/chronic toxic stress in men with prostate cancer.

263 Background: Allostatic load (AL)/chronic toxic stress is linked to a higher risk of adverse cancer-specific and cardiac events in prostate cancer (PC) patients especially non-Hispanic Blacks (NHBs). We hypothesize that NHBs experience more adverse social determinants of health (SDOH) that increases this AL. Methods: We included men≥18 years diagnosed with PC (2010-2022). Individual-level SDOH with 19 covariates across 4 domains was obtained. Pre-PC diagnosis AL was calculated as an ordinal measure (0-11). Components and cutoffs for the AL score: Each measure above the cutoff add 1 point to AL. Systolic blood pressure (BP) ≥140 mmHg, diastolic BP ≥90 mmHg, heart rate >100 bpm, total cholesterol (chol) ≥240 mg/dl, high-density lipoprotein chol ≤50 mg/dl, triglycerides ≥150 mg/dl, glycated hemoglobin ≥6.5, body mass index ≥30 kg/m2, glucose ≥110 mg/dl, C-reactive protein >3 mg/L and interleukin-6 >1.8 pg/ml. A gradient-boosting Machine Learning model ranked AL predictors using SHAP scores (SS). Cubic splined from logistic regressions defined SDOH adversity cutoffs. Results: Among 4,258 patients (886 NHB), the median age was 69 (IQR 63-77). Most were former smokers (44.2%), and the median Charlson comorbidity score was 4 (IQR 2-7). In NHBs, the SDOH variables among the top 5 overall predictors of AL were annual income (SS=0.10), neighborhood murder index (SS=0.07), neighborhood median income (SS=0.06), and neighborhood car theft index (SS=0.05). Considering all the SDOH features analyzed, NHBs faced adversity in 12 of 19 SDOH features (63%; Table). Conclusions: SDOH related to the neighborhood, built environment, and economic stability, are crucial predictors of pre-PC diagnosis AL in NHBs. [Table: see text]

Bundled insurance coverage and asymmetric information: Claim patterns of automobile theft insurance in Taiwan

In the presence of moral hazard, automobile theft insurance claims may be fabricated to compensate for losses incurred during traffic accidents. Using a unique national dataset, we compare the claim probabilities for automobile theft insurance among policyholders with bundled automobile insurance coverage (both automobile theft insurance and automobile physical damage insurance) and policyholders with only automobile theft coverage. We find that policyholders with only automobile theft coverage have a significantly higher claim probability than those with bundled coverage. In addition, we find that automobile theft insurance with (without) stolen parts endorsement is associated with higher claim probabilities for total and partial losses (only total losses). We further investigate the effects of car brands and show that Mazda, BMW, and Toyota are associated with significantly higher claim probabilities for both total and partial losses among policyholders with only automobile theft insurance. The results of this study point to a crucial policy implication for insurers. When determining the rating structure of discrimination premium setting, they should consider whether policyholders have bundled insurance policies or not, in addition to car brands.

Effects of Internal Forced Displacement on Crime: Evidence from Colombia

Internal forced displacement, a consequence of territorial control strategies by armed groups, has resulted in profound socioeconomic challenges for receiving areas. Approximately eight million people have been affected in Colombia, where internal conflict and criminal networks have prevailed for over five decades. This paper explores the relationship between internal forced migration and crime rates in Colombian municipalities from 2003 to 2016, focusing on spatial dynamics. The study utilizes a spatial panel model and considers five crime categories: homicides, kidnapping, personal injuries, automobile theft, and residential burglary. The results reveal significant associations between forced displacement and certain types of crime, highlighting the importance of spatial analysis in understanding the interaction between migration and crime. The findings offer valuable insights for policymakers and researchers, facilitating informed policy interventions and community initiatives to address the repercussions of internal migration on crime dynamics.

A Framework Solution for Vehicle Theft Detection by Integrating NFC With a Blockchain-Based System

Vehicle theft is a widespread and costly problem with thousands of cars stolen annually, impacting privacy, the economy, and security. Conventional database systems have proven unreliable, enabling a thriving market for stolen vehicles. In response, our study presents an innovative solution, leveraging the security of blockchain technology. By utilizing the Ethereum Virtual Machine (EVM) and Smart Contracts, our system is designed to thwart attacks, including Distributed Denial of Services (DDoS) attacks. Notably, Near Field Communication (NFC) enables the secure transmission of sensitive data for verification. Our research aims to evaluate the real-world impact of this technology, considering factors such as improvements in data security and the efficiency of the reporting process. One of the most notable outcomes of our proposal is the substantial reduction in reporting time for car theft. While conventional reporting typically takes several hours, our system streamlines the process to less than 1 minute. This innovation offers significant benefits to vehicle owners, law enforcement agencies, and the broader community.

“They are kids, they’re making bad choices, but they are not bad kids”: motivations and deterrents for joyriding amongst Australian youth

ABSTRACT Car theft and joyriding are becoming increasingly common in regional areas of Australia. Whilst the consequences of these actions can be fatal, surprisingly little is known about the motivations for young people who engage in these behaviours. This exploratory study draws from 17 in-depth interviews that were conducted as part of a pilot intervention program aimed at adolescents either already engaged or susceptible to car theft and joyriding behaviours. The findings suggest that joyriding predominately attracts disenfranchised youth who lack opportunities for education, employment, and leisure. For these adolescents, joyriding emerges to counterbalance disadvantage and alleviate the monotony in their lives. Interviewees also provide suggestions for deterring joyriding, such as providing young people with occupational opportunities that allow them to serve as role models to themselves and others and adrenaline-based activities to replace the thrills of joyriding.

Three-Level Car Security System with GPS Tracker Using IoT

Nowadays, car theft is common and because of that, there is a need to invest on a car security system. Hence, this work focusses on developing a Three-level car security system with GPS Tracker using IoT. Arduino Mega 2560 module act as a microcontroller for RC522 RFID module and R307 fingerprint scanner module which is for the first and second level security. A 4×3 matrix keypad and NEO-6M GPS are integrated with the NodeMCU ESP8266 Wi-Fi module for the security and GPS tracking system. The car security system consists of three level security which are RFID tag, fingerprint scanner and keypad password. Upon entering the car, the owner has to tag the RFID before scanning the fingerprint and entering the password. The owner is given three chances to enter the password or else, the GPS tracking is activated. In worst case scenario, the thief might enter the car by force and steal the car. In this case, the owner shall receive a notification via text message on Blynk application and email for second notification. Furthermore, the location of the car can also be obtained from the NEO-6M GPS tracking system which is linked to the Blynk application on the owner’s mobile phone. The Blynk application shall display the location of the car on Google maps together with its latitude and longitude. It is shown from this work that the car security system provides a sufficient level of security to avoid car theft. In addition, the GPS tracking system is able to detect the location of the car which is displayed on the Blynk application installed in car owner’s mobile phone.

Design and Implementation of an Intelligent Safety and Security System for Vehicles Based on GSM Communication and IoT Network for Real-Time Tracking

In recent years, the surge in car theft cases, often linked to illicit activities, has become a growing concern. Simultaneously, countries grappling with oil shortages have shifted towards converting vehicles to run on liquid propane gas, presenting new safety challenges for car owners. This paper introduces a novel integrated intelligent system designed to address the challenges of car theft and safety concerns associated with gas-based vehicles. By seamlessly integrating these concerns into a single system, it aims to achieve significantly improved performance compared to traditional alarm systems. The proposed system consists of three primary parts: the car security subsystem, an Internet of Things (IoT)-based real-time car tracking subsystem, and the car safety subsystem. Utilizing key technologies such as the Arduino Microcontroller, Bluetooth module, vibration sensor, keypad, solenoid lock, GSM module, NodeMCU microcontroller, GPS module, MQ-4 gas sensor, flame sensor, temperature sensor, and Bluetooth module, the system aims to provide a comprehensive solution for the mentioned issues. Furthermore, the vibration sensor plays a crucial role in identifying unauthorized vehicle operations. Its significance lies in detecting the vibrations emanating from the running engine. Concurrently, other modules and sensors are utilized for real-time tracking and enhancing vehicle safety. These measures include safeguarding against incidents like fire outbreaks or gas leaks within the gas container. Finally, after assembling the system, a practical test was conducted, yielding favourable performance results. This paper describes a meaningful step towards improving the protection and safety for the cars, simultaneously addressing the stealing prevention and gas-related accident alleviation.

Automatic Vehicle Identification System Using RFID Electronic Tag for Traffic IoT Applications

RFID technology has emerged as one of the most prominent and transformative technologies globally. Its diverse applications have significantly enhanced our daily lives, ensuring greater convenience and enhanced security. The focus of the present study revolves around leveraging this remarkable RFID technology to counter car theft and unauthorized vehicle usage. The project centers on employing Arduino Nano Technology, a cost-effective solution compared to other available technologies, to address this issue effectively. The core concept involves the utilization of RFID tags, which are scanned by an RFID scanner to store crucial data within the tag. This data is compared against the stored information of authorized personnel. The primary objective is to identify stolen or unauthorized vehicles swiftly. By harnessing the power of Arduino Nano, this project not only becomes affordable but also promises efficient outcomes. The components crucial to the project's success include the RFID technology itself, the Arduino Nano board, the SD card module, and the RTC module DS3231. Working in synergy, these components enable seamless data transfer and comparison, facilitating timely decision-making when discrepancies are detected. With the integration of RFID technology, the security and tracking capabilities of this system hold immense potential for curbing car theft and unauthorized vehicle usage. By ensuring that the scanned RFID data aligns with authorized ownership, appropriate measures can be promptly taken to mitigate any potential security breaches. This innovative application of RFID technology in conjunction with Arduino Nano highlights the potential to revolutionize vehicle security and surveillance measures, creating a safer and more reliable automotive landscape.

Finger Print Sensing Vehicle Starter

The fingerprint vehicle starter project aims to increase the security of vehicles by using biometric authentication technology. Biometrics system can be used as a good and effective security option. An important and very reliable human identification method is fingerprint identification. Vehicle safety has become a serious problem as the frequency of crime has increased. Vehicle keys are a big concern these days since they are easily forgotten or lost when carried. At start, this technology lets the customer to authenticate by scanning their unique fingerprint. The system uses a fingerprint scanner to identify the authorized user of the vehicle, allowing them to start the engine. This project is designed to prevent car theft and improve user convenience, as drivers will not need to carry keys with them. The system allows multiple users to register as authorized users. When into monitoring mode, the system checks for users to scan. On scanning, the system checks if user is authorized user. The system is implemented using an Arduino microcontroller and a fingerprint sensor module, which communicate with the vehicle's ignition system. The project's success is evaluated based on its accuracy in identifying the authorized user and its reliability in preventing unauthorized access to the vehicle. This project has the potential to significantly improve vehicle security and enhance user experience. This provides safe and worry-free way to begin the engine or automobile. The fingerprint vehicle starter project aims to increase the security of vehicles by using biometric authentication technology. Biometrics system can be used as a good and effective security option. An important and very reliable human identification method is fingerprint Identification.

Smart Remote Transit Vehicle Monitoring with Emission Alert and Secured Access Using IOT

Abstract: The research paper focuses on addressing automobile theft by proposing a framework utilizing the Internet of Things (IoT), GPS, and GSM technologies. This system allows vehicle owners to track and monitor their vehicles at any time from anywhere, improving security against professional thieves. The IoT sends information about the vehicle's status to the guardian or owner, while GPS provides the vehicle's current location. In case of theft, the fuel supply can be gradually cut off by sending a message, disabling the vehicle, and updating data to the Google Firebase server. An RFID card is provided to start the vehicle, and an Android app is developed using the MIT AppInventor tool for monitoring maps and notifications. Additionally, emission levels are measured and updated to the cloud, and a panic button is included for driver assistance in emergencies. This proposed system enhances existing anti-theft measures while offering innovative features for better vehicle security and management.

A Crime Prediction Model/Tool for Hotspot Mapping

The hotspot map is a popular analytics tool used to help law enforcement and crime reduction resources determine where to focus. Essentially, the hotspot map is used as a data-driven crime map to identify high-crime areas and places where police and other criminal activities should be used. The project uses crime data from a period before (already past) a certain date to create heat maps and test their accuracy in predicting what will happen next. Compare hotspot mapping accuracy with maps used to measure crime issues (thematic mapping of the census output area, spatial ellipses, grid thematic mapping, and core density estimation) and by crime type – the four crime types (crime, crime, car theft, and car theft)..

Security System For Motorcycle Using Raspberry Pi and Fingerprint With Mobile-Based Finite State Machine (FSM) Method

Data from the BPS (Central Statistical Agency) show that private car theft in Indonesia is on the rise year after year, especially for two-wheeled vehicles or motorcycles. According to the BPS Crime Statistics Report, there were around 35,000 motor vehicle theft events in Indonesia in 2017 and 38,000 instances in 2018. People's concerns regarding the security of these two-wheeled vehicles are growing as a result. This study presents a fingerprint- and Raspberry Pi-based motorcycle security system. Bikes may be monitored, and their ignitions can be controlled remotely using a mobile-based Finite State Machine (FSM) technique. The Neo 6 GPS module will send longitude and latitude in real time to the Android smartphone application, which generates a map or location point so that it will send notifications if there is movement on the motorcycle. The voltage sensor connected to the Raspberry Pi circuit can detect the motor voltage. A system that uses the FSM (Finite State Machine) approach to identify changes in location data from designated parking lots and deliver messages to a push bullet is the study's output. Controlling the motorcycle ignition, which may remotely switch off the motorcycle when one is taken, is another way to provide early notice.

Insurance technopolitics: Car theft, recovery, and tracking systems in São Paulo

In response to high levels of car theft, insurance companies in São Paulo have developed new systems and technologies for tracking and recovering stolen vehicles. These interventions are driven by an insurance rationality that seeks to manage risk and ensure these companies’ profitability. However, this article draws on the notion of technopolitics to argue that the tracking devices and other technologies mobilized in this way also exercise their own agency. They help to mediate and reorganize the power dynamics and relations between diverse actors who operate within São Paulo’s stolen car market and vehicle recovery processes, presenting both challenges and opportunities for each as they pursue their respective aims. The notion of ‘insurance technopolitics’ emphasizes this conjunction between risk governance and the contingent, technologically mediated relationships and conflicts to which it may give rise.

El robo de autos en Reynosa: análisis espacial desde la teoría de las actividades rutinarias y del patrón del crimen

This article analyzes the spatial behavior of social and economic factors associated with car theft in Reynosa, Tamaulipas, Mexico. For this, the data of car theft reports issued (from January 2016 to December 2018) before the Attorney General’s Office of the state of Tamaulipas were analyzed. The information on the social and economic variables was obtained from the Census of Population and Housing 2020 at the level of basic geostatistical area and the National Statistical Directory of Economic Units. The methodology consisted of a negative binomial regression, a simple regression, and a geographically weighted regression, both Poisson types to incorporate the non-stationarity spatial component. The results indicate that restaurants and banks are crime-attracting nodes and that the variables of routine activities present heterogeneous spatial patterns depending on the area of the city where they are present.

Study on Improving the Safety and Performance of Vehicle Traffic Assistance Systems

More intricate applications for road safety have come from advances in information technology. These systems offer a lot of potential for improving road transportation. The integrated method provided in this research addresses two primary topics: protection and performance. As a result, it is recommended that Vehicle Traffic Assistance (VTA) for rural and intercity contexts be developed and implemented. VTA is made up of an electronic control unit (ECU) that receives data from cameras positioned strategically around the vehicle to recognise traffic conditions and deliver data to the ECU. In the event that the driver deviates from the traffic laws, the ECU compares the input data from the cameras to reference data stored in the ECU memory and assists the driver by offering instructions through the output speaker device. VTA not only assists drivers, but it also monitors and prevents them from breaking traffic laws. It also ensures safety by personalising driver information in the ECU to avoid car theft.