List of Titles

Crime concentration in Perth CBD : A comparison of officer predicted hot spots, data derived hot spots and officer GPS patrol data

- Oatley, Giles, Williams, Stephen, Barnes, Geoffrey, Clare, Joseph, Chapman, Brendan

Authors: Oatley, Giles , Williams, Stephen , Barnes, Geoffrey , Clare, Joseph , Chapman, Brendan
Date: 2019
Type: Text , Journal article
Relation: Australian Journal of Forensic Sciences Vol. 51, no. sup1 (2019), p. S136-S140
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Description: In an applied criminology context, recent meta-analyses and randomized control trials have demonstrated the benefits of targeting police patrols at hot spots or concentrations of street level crime and disorder. This study asked a group of 79 police officers from Perth to make a prediction, based on their experience, of where hot spots of crime would occur in the near future. Officer-defined hot spots were then compared with hot spots derived from police crime data over the preceding 24 month period. Finally, officer patrol time was tracked using a GPS-enabled smart phone and overlayed against both types of hot spot. This analysis indicates that police officers should be supported with hot spot mapping tools which identify data derived micro-places with persistent issues. Analysis also reveals officers patrol both their own and data-derived hot spots regularly; however, they only stay for a matter of a few minutes. These short stays are contrary to best evidence, which dictates officer patrols in hot spots should last for approximately 15 minutes in order to create both initial and residual deterrence.

The current and future role of smart street furniture in smart cities

- Nassar, Mohamed, Luxford, Len, Cole, Peter, Oatley, Giles, Koutsakis, Polychronis

Authors: Nassar, Mohamed , Luxford, Len , Cole, Peter , Oatley, Giles , Koutsakis, Polychronis
Date: 2019
Type: Text , Journal article
Relation: IEEE Communications Magazine Vol. 57, no. 6 (2019), p. 68-73
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Description: Recently, street furniture, including bins, seats, and bus shelters, has become smart as it has been equipped with environmental sensors, wireless modules, processors, and microcontrollers. Accordingly, smart furniture is expected to become a vital part of the IoT infrastructure and one of the drivers of future smart cities. This work focuses on how smart street furniture can be exploited within the IoT architecture as a basis of recommender systems, toward achieving smart cities' different components. We present and discuss recent relevant work as well as the key challenges and opportunities for future research. We explain that much work is still required when it comes to combining scalability, real-time processing, smart furniture, and recommender systems.

A review and recommendations for the integration of forensic expertise within police cold case reviews

- Chapman, Brendan, Keatley, David, Oatley, Giles, Coumbaros, John, Maker, Garth

Authors: Chapman, Brendan , Keatley, David , Oatley, Giles , Coumbaros, John , Maker, Garth
Date: 2019
Type: Text , Journal article , Review
Relation: Journal of Criminal Psychology Vol. 10, no. 2 (2019), p. 79-91
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Description: Purpose: Cold case review teams and the processes that they adopt in their endeavour to solve historic crimes are varied and largely underreported. Of the limited literature surrounding the topic of cold case reviews, the focus is on clearance rates and the selection of cases for review. While multiple reports and reviews have been undertaken and recommend that the interface between investigators and forensic scientists be improved, there is little evidence of cold case teams comprised of a mixture of investigators and scientists or experts. With the growing reliance on forensic science as an aide to solvability, the authors propose that the inclusion of forensic scientists to the central cold case investigation may be a critical factor in future success. The paper aims to discuss this issue. Design/methodology/approach: To support the proposed approach, the authors conducted a review of the current literature seeking insight into the reported make-up of cold case teams. In conjunction with this, the authors reviewed a number of commissioned reports intended to improve cold case reviews and forensic services. Findings: While many of the reviewed reports and recommendations suggested better integration with scientists and external expertise, little evidence of this in practice was reported within published literature. Open dialogue and cross pollination between police investigators and forensic scientists are likely to mitigate biases, inform case file triage and better equip investigations with contemporary and cutting-edge scientific solutions to the evidence analysis for cold cases. Furthermore, with respect to scientists within academia, large pools of resources by way of student interns or researchers may be available to assist resource-sparse policing jurisdictions. Originality/value: To the authors’ knowledge, this is the first peer-reviewed recommendation for the consideration of integrated forensic scientists within a cold case review team. Multiple reports suggest the need for closer ties, but it is the anecdotal experience of the authors that the benefits of a blended task force approach may yield greater success. © 2020, Emerald Publishing Limited.

Adaptive low-power wireless sensor network architecture for smart street furniture-based crowd and environmental measurements

- Nassar, Mohammed, Luxford, Len, Cole, Peter, Oatley, Giles, Koutsakis, Polychronis, IEEE

Authors: Nassar, Mohammed , Luxford, Len , Cole, Peter , Oatley, Giles , Koutsakis, Polychronis , IEEE
Date: 2019
Type: Text , Conference proceedings
Relation: 2019 IEEE 20th International Symposium on a World of Wireless, Mobile and Multimedia Networks
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Description: Street furniture such as bins, seats and bus shelters can become "smart" with the inclusion of wireless sensor nodes, which consist of environmental sensors, wireless modules, processors and microcontrollers. One of the most crucial challenges for smart street furniture is how to manage power consumption efficiently without affecting data freshness. In this work, we propose a novel Wireless Sensor Network (WSN) architecture for smart street furniture. Unlike existing WSNs which are based on a one-way communication model between wireless sensor nodes and the server, the proposed architecture employs a two-way communication model and a dynamic adaptation of the time interval of measurements to balance between power consumption and data updates. Our approach also provides a real-time low-power design for wireless sensor nodes which efficiently communicate the updated data instead of sending the same data on a regular basis. To the best of our knowledge, this is the first work in the relevant literature which extends the functionality of the wireless module in wireless sensor nodes to act not only as a station sending environmental data but also as soft Access Point (AP), sensing MAC addresses and WiFi signal strengths from surrounding WiFi-enabled devices. We have conducted experiments on the Murdoch University campus and our results show that our proposal improves lifetime of wireless sensor nodes up to 293% compared to static architectures similar to the ones that have been proposed in the literature. Moreover, network bandwidth is improved up to 38% without affecting data freshness. Finally, storage space for the database at the server is reduced up to 99%.
Description: E1

Behaviour tracking : using geospatial and behaviour sequence analysis to map crime

- Keatley, David, Arntfield, Michael, Gill, Paul, Clare, Joe, Oatley, Giles, Bouhana, Noemie, Clarke, David

Authors: Keatley, David , Arntfield, Michael , Gill, Paul , Clare, Joe , Oatley, Giles , Bouhana, Noemie , Clarke, David
Date: 2021
Type: Text , Journal article
Relation: Security Journal Vol. 34, no. 1 (2021), p. 184-201
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Description: Crime is a complex phenomenon. To understand the commission of crime, researchers must map both the temporal and the spatial processes involved. The current research combines a temporal method of analysis, Behaviour Sequence Analysis, with geospatial mapping, to outline a new method of integrating temporal and spatial movements of criminals. To show how the new method can be applied, a burglary scenario was used, and the movements and behaviours of a criminal tracked around the property. Results showed that combining temporal and spatial analyses allows for a clearer account of the process of a crime scene. The current method has application to a large range of other crimes and terrorist movements, for instance between cities and movements within each city. Therefore, the current research provides the foundation framework for a novel method of spatio-temporal analyses of crime. © 2019, Springer Nature Limited.

Non-invasive smartphone use monitoring to assess cognitive impairment

- Thang, Nguyen, Oatley, Giles, Stranieri, Andrew, Walker, Darren

Authors: Thang, Nguyen , Oatley, Giles , Stranieri, Andrew , Walker, Darren
Date: 2021
Type: Text , Conference paper
Relation: 13th International Conference on Computer and Automation Engineering, ICCAE 2021 p. 64-67
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Description: Background: There are many tests for the early detection of Mild Cognitive Impairment (MCI) to prevent or delay the development of dementia, particularly amongst the elderly. However, many tests are complex and are required to be performed repeatedly. Cognitive assessment apps for a smartphone have emerged, but like other tests, they require the user to perform complex tasks like drawing time on a clock. Few studies have explored non-invasive ways of tracking and assessing MCI without having the user perform specific tests. Objective: This research ultimately aims to develop an app that runs in the background and collects smartphone usage data that correlates well with MCI test results. The focus of this preliminary study was to develop an app that collects usage data and common MCI questionnaires to see if usage data between people varied, and to establish associations between phone usage and cognitive tests results. Method: An android application was developed to gather data over three weeks by three volunteers (authors). Usage data collected included: SMS and call log, accelerometer, location, app usage, self-report. Cognitive tests implemented were Stroop, Go/No Go tests and absent-mindedness questionnaires. Due to the small sample size and Covid-19 restrictions (October 2020), location data was not reliable. SMS text was not collected for privacy reasons. Results: App categories can differentiate people, but the app usage cannot be used to distinguish people. © 2021 IEEE.

Wifi-based localisation datasets for No-GPS open areas using smart bins

- Nassar, Mohamed, Hasan, Mahmud, Khan, Md, Sultana, Mirza, Hasan, Md, Luxford, Len, Cole, Peter, Oatley, Giles, Koutsakis, Polychronis

Authors: Nassar, Mohamed , Hasan, Mahmud , Khan, Md , Sultana, Mirza , Hasan, Md , Luxford, Len , Cole, Peter , Oatley, Giles , Koutsakis, Polychronis
Date: 2020
Type: Text , Journal article , Data article
Relation: Computer Networks Vol. 180, no. (2020), p. 1-5
Full Text: false
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Description: In recent years, Wifi-based localisation systems have gained significant interest because of the lack of Global Positioning System (GPS) signal in indoor and certain open areas. Over the past decade, many datasets have been introduced to enable researchers to compare different localisation techniques. Existing datasets, however, have failed to cover open areas such as parks in cases where GPS is still unavailable, and there is a lack of Wifi access points. Also, the existing datasets only focus on getting Wifi fingerprint collected and labelled by users. To the best of our knowledge, no dataset provides Received Signal Strengths (RSS) collected by Wireless Access Points (APs). In this work, we offer two datasets publicly. The first is the Fingerprint dataset in which four users generated 16,032 accurate and consistently labelled WiFi fingerprints for all available Reference Points (RPs) in a central and busy area of Murdoch University, known as Bush Court. The second is the APs dataset that includes 2,450,865 auto-generated records received from 1000 users' devices, including the four users, associated with Wifi signal strengths. To overcome the Wifi coverage problem for the Bush Court, we attached our previously designed Wireless Sensor Nodes (WSNs) to existing garbage bins, enabling them to provide real-time environmental sensing and act as soft APs that sense MAC addresses and Wifi signals from surrounding devices.

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