Search results

The purpose of this paper is to quantify the effect of the enforcement, which was carried out with ANPRs, on seat belt use. Though the Seat belt Act was enacted in 1992, it did not lead to an expected increase in seat belt use in Turkey including Sanliurfa, which is one of the immense provinces with a population of over 2m. The Sanliurfa Police Department set in an enforcement campaign, in which automatic number plate recognition (ANPR) cameras were used to facilitate an increment in using seat belts in the city center. Under the police leadership, seat belt use enforcement campaign was hugely publicized and sustained throughout the city.

The ANPRs did not have a feature to detect seat belt wearing automatically. Thus, this study tested whether automated plate recognition cameras have a deterrence effect on seat belt usage. To assess the efficacy of this enforcement project, the authors employed a pre/post-implementation design. For this study, the records of the 11 ANPR camera sites, 2 non-camera sites and 2 control sites were utilized.

The results of this study revealed that the seat belt use rate was around 8 percent, before camera enforcement in Sanliurfa. Overall increases were 12 percent during the warning period, 60 percent for the beginning period and 78 percent three months after enforcement began at camera sites. One-way ANOVA results suggested the differences between means of seat belt use counts were statistically significant F (3, 61,596)=15,456, p=0.000.

The findings suggest that there are several reasons for the substantial increase in the seat belt use rate. The first reason for the success of the cameras was their deterrent effect on the drivers, because the drivers were aware that the traffic offense had become readily observable via camera detection in the intersections, and the drivers did not want to be penalized. Second, it is considered that a well-organized publicity of the cameras made a significant contribution to the effectiveness of the enforcement by increasing perceived detection risk. Finally, it is considered that the reason behind the sudden increase in seat belt use was the red-light cameras that had been already in use in Sanliurfa. Namely, the experience of the drivers about camera enforcement gave rise to the rapid decrease in seat belt violation rate in the warning period.

Using cameras (automatic or not) for seat belt enforcement and publicizing this enforcement can help to save resources and lives.

This study found a lot of news about similar enforcement on the internet, but no study was found in the literature that reveals if the enforcement can produce an effective result. Thus, this is the first study in Turkey, may be in the world, that evaluated if cameras of the ANPRS can generate effective seat belt enforcement. Furthermore, the study betokened that traffic violations, which cannot be automatically detected by cameras such as cell phone use and smoking in a vehicle can be effectively enforced by non-automatic cameras. Therefore, we believe that the study will contribute policing and the traffic safety literature.

Technology is an important driver of organizational change and often strategically used to facilitate adaptations in organizational processes and cultures. While the link between technological and organizational change is widely recognized, the role of macro‐context for this link remains undervalued. Based on data from technology implementations in European police forces the paper aims to illustrate the importance of integrating analyses of the macro‐context to understand the complexity of technology driven organizational change.

The authors conducted 56 interviews and five focus groups with police officers from 13 countries on two of the major technology trends in European police forces: automatic number plate recognition systems (ANPR) systems and social media. They further conducted site visits to police forces in The Netherlands and the United Kingdom to observe technology usage first hand. Comparing accounts across countries they analyzed how macro‐context impacted adoption decisions and implementation processes. In this analysis they concentrated on the five macro‐contextual factors in the PESTL framework, i.e. political, economic, social, technological and legal factors.

In analyses of ANPR systems and social media the paper details how the macro‐context of police organizations impacted decisions to adopt a technology as well as the intra‐organizational alignments of processes and structures.

Organizational decision makers and implementers need to be aware not only of the strong agency of technology for organizations' structure and processes, but also of the relevance of the organizational macro‐context for the process and impact of technology implementations on the organizational as well as individual level.

The paper illustrates the impact of the macro‐context of organizations in shaping the link between technological change and organizational change.

Particular attention to the issue of information management will be required to meet the expected growth in IoT-devices and the data they generate. As government agencies start collecting and using such information, they must also deal with the issue of privacy, to comply with laws and regulations. The approach discussed here shows that record-keeping principles may form part of a solution to the issue of managing IoT-data for government agencies.

This study uses the generally accepted record-keeping principles as a basis for a high-level discussion on how IoT-data can be managed. This is followed by a presentation and discussion on how the Norwegian record-keeping standard, Noark, can be extended to highlight practical issues.

Record keeping has principles that are relevant to the management of IoT-data. Further an implementation of the chosen use-cases is possible based on an existing record keeping standard. Record keeping is one of many information science approaches that can manage IoT-data.

The main limitations are that the discussion cannot cover all types of IoT-devices, nor can all issues be captured with a limited choice of examples. The results should be seen within the context of the types of devices discussed and limited to the chosen use-cases. However, the level of abstraction used means the results may be applicable to similar scenarios.

The approach shows that record-keeping principles may be used as an approach to manage IoT-data. This discussion is useful when compared with other information science approaches, e.g. big-data or semantic Web approaches. The practicalities of a record-keeping approach are also discussed and relevant strengths and weaknesses are showed.

The purpose of this paper is to consider the existing literature surrounding the use of technology in today’s society to inform future developments across emergency services. Reference to the Police Service in particular will have a resonance for many other public agencies who are utilising more and more technology.

Literature from a policing background will be reviewed to discover the positive impacts and benefits attached to its use, the potential obstacles to its implantation, and how lessons from one agency may be of benefit to others.

The findings suggest that there appears to be attention required in the application of technology by public agencies, namely, workforce culture, training and budgets, and legislation which need to be addressed if the use of technology by public agencies is to be successful.

This paper seeks to learn lessons for the implementation technology by a public agency, namely, the police, in an attempt to inform other public bodies. By doing so, it is believed the lessons learned will make the application of such technologies more effective.

This paper aims to present collection and analysis of heterogeneous urban traffic data, and integration of them through a kernel-based approach for assessing performance of urban transport network facilities. The recent development in sensing and information technology opens up opportunities for researching the use of this vast amount of new urban traffic data. This paper contributes to analysis and management of urban transport facilities.

In this paper, the data fusion algorithm are developed by using a kernel-based interpolation approach. Our objective is to reconstruct the underlying urban traffic pattern with fine spatial and temporal granularity through processing and integrating data from different sources. The fusion algorithm can work with data collected in different space-time resolution, with different level of accuracy and from different kinds of sensors. The properties and performance of the fusion algorithm is evaluated by using a virtual test bed produced by VISSIM microscopic simulation. The methodology is demonstrated through a real-world application in Central London.

The results show that the proposed algorithm is able to reconstruct accurately the underlying traffic flow pattern on transport network facilities with ordinary data sources on both virtual and real-world test beds. The data sources considered herein include loop detectors, cameras and GPS devices. The proposed data fusion algorithm does not require assumption and calibration of any underlying model. It is easy to implement and compute through advanced technique such as parallel computing.

The presented study is among the first utilizing and integrating heterogeneous urban traffic data from a major city like London. Unlike many other existing studies, the proposed method is data driven and does not require any assumption of underlying model. The formulation of the data fusion algorithm also allows it to be parallelized for large-scale applications. The study contributes to the application of Big Data analytics to infrastructure management.

Vehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time.

This paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles.

Experiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method.

To reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.

The purpose of this paper is to document the diffusion of license plate readers (LPRs) in the USA, examining the variety, evolution and tracking of their uses through a national survey.

This study employs a national, stratified, representative survey of US law enforcement agencies with 100 or more officers.

LPR technology is currently used by at least two-thirds of larger police agencies, which represents a more than threefold increase in LPR acquisition in the last 10 years. The number of LPRs per agency, while small (about eight on average), has also more than doubled. Federal and state funding, advocacy by law enforcement leaders, and the intuitive appeal of LPRs have likely contributed to this rapid adoption. While LPRs are still primarily used to detect and recover stolen automobiles in patrol, their use has expanded into other types of investigative and security functions. Despite the increased use and numbers of LPRs in policing, their use is highly discretionary and infrequently tracked.

LPRs continue to be widely used in law enforcement, despite a lack of strong research evidence for their crime prevention benefits. Further studies are needed on the most effective ways for agencies to utilize small numbers of LPRs and the potential return on investment for acquiring larger numbers of the devices.

This study tracks the history of LPR diffusion and use and goes beyond prior law enforcement surveys by examining specific uses of LPRs and the extent to which agencies track their uses and outcomes.

This article explores how homicide detectives make sense of and manipulate multiple physical, digital and informational artefacts when assembling case narratives. The authors introduce the concept of mosaicking to illuminate how different modes of information, deriving from different investigative methods, are used in concert at key moments of the investigative process – defining what type of crime has occurred; the incrimination and elimination of suspects; and decisions to charge key suspects.

The data qualitatively analysed include several hundred case papers, interview transcripts (n = 144) and detailed ethnographic fieldnotes relating to 44 homicide investigations across four police services. These were collected during a four-year ethnographic study of the use of forensic sciences and technologies (FSTs) in British homicide investigations.

Mosaicking describes how investigators blend and combine information, intelligence and evidence generated via different techniques and methods, to make sense of “who did what to whom and why?” Through processes of convergent and divergent mosaicking, detectives are able to “lean” on different kinds of material to reinforce or connect key points of evidence or intelligence.

The findings fill a gap in knowledge about how investigators blend and composite diverse sources of information in the construction of case narratives. The findings present a more complex and nuanced understanding of the epistemological and interpretative work conducted by contemporary detectives, given the array of investigative technologies they increasingly have at their disposal.

This chapter aims to make a contribution to recent debates on the ‘governance of security’ (Johnston & Shearing, 2003) by drawing upon empirical research conducted by the author and other writers on ‘plural policing’ and the construction of closed circuit television (CCTV) surveillance networks. The chapter attempts to avoid the tendency in some of the ‘governmentality’ literature to ‘airbrush out the state’ (Hughes, 2007, p. 184), whilst at the same time showing that the aims and intentions of dominant state forces and elites are not always realised in practice. The chapter also tries to avoid any simplistic notion of a shift in policing strategies from ‘crime fighting’ to ‘risk management’. The aim instead is to show how the construction of surveillance networks is blurring the boundaries of the ‘public–private’ divide along the ‘sectoral’, ‘geographical’, ‘spatial’, ‘legal’ and ‘functional’ dimensions (Jones & Newburn, 1998), giving rise to a plural policing continuum.

The purpose of this article is to inform stakeholders about the Anti-Money Laundering Act of 2020 (AMLA), explain its impact on the U.S. anti-money laundering (AML) regime, and highlight critical updates for financial institutions.

The article provides an overview of the AMLA, and specifically addresses three key components: (1) the development of uniform beneficial ownership requirements and the creation of a beneficial ownership registry at the Financial Crimes Enforcement Network (FinCEN); (2) the expansion of FinCEN’s powers and the Bank Secrecy Act/AML program requirements; and (3) new subpoena powers with potential extraterritorial effect granted to the U.S. Secretary of the Treasury and the U.S. Attorney General for documents located at foreign banks that have a correspondent banking account in the U.S. The article also notes the purpose and goals of the AMLA.

The AMLA is the first major overhaul of the U.S. AML regime since the 2001 USA PATRIOT Act, and is designed to strengthen national security, protect the financial system, and simplify compliance obligations. The beneficial ownership reporting requirements represent an effort to combat illicit financial activity conducted by shell companies formed and registered in the U.S.

The article provides financial institutions with a brief overview of a lengthy new law that will impact their AML compliance obligations. Financial institutions should be on alert for forthcoming regulations.