Information and communication technologies are not value-neutral. I examine two domains, public health surveillance and sustainability, in five papers covering: (i) the design and development of a software package for computer-assisted outbreak detection; (ii) a workflow for using simulation models to provide policy advice and a list of challenges for its practice; (iii) an analysis of design documents from three smart home projects presenting intersecting visions of sustainability; (iv) an analysis of EU-financed projects dealing with sustainability and ICT; (v) an analysis of the consequences of design choices when creating surveillance technologies. My contributions include three empirical studies of surveillance discourses where I identify the forms of action that are privileged and the values that are embedded into them. In these discourses, the presence of ICT entails increased surveillance, privileging technological expertise, and prioritising centralised forms of knowledge. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Manuscript. Paper 5: Manuscript.</p>

Wireless Sensor Network (WSN), a collection of “sensor nodes” promises to change the scientist’s approach of gathering the environmental data in various fields. Sensor nodes can be used for non-stop sensing, event detection, location sensing and local control of actuators, this concept gives surety to many latest application areas like agriculture, military, home or factory automation, logistics and so on. Remote surveillance and measurement missions can be performed by using WSNs. The hot research topic now-a-days is to make such networks remotely controllable and adaptive to the environment and mission. The work carried out in this thesis is the development of a surveillance application using TinyOS/nesC. The purpose of this application is to perform event-detection mission by using any one of the built-in sensor on Mica2 motes as well as a setup protocol is designed to make the WSN remotely controllable and adaptive to the mission. In this thesis, an experimental work is also performed using TinyDB to build up a surveillance system whose purpose is to detect and count the total number of person present at any time in a given room and to view the results at a remote place. Besides these two system applications, a comparative study between TinyDB and nesC is described which concludes that more hardware control can be achieved through nesC which is a more power efficient platform for long-term applications.

Video surveillance systems are playing an increasing role in preventing and investigating crime, protecting public safety, and safeguarding national security. In a typical surveillance installation, a human operator has to constantly monitor a large array of video feeds for suspicious behaviour. As the number of cameras increases, information overload makes manual surveillance increasingly difficult, adding to other confounding factors like human fatigue and boredom. The objective of an intelligent vision-based surveillance system is to automate the monitoring and event detection components of surveillance, alerting the operator only when unusual behaviour or other events of interest are detected. While most traditional methods for trajectory-based unusual behaviour detection rely on low-level trajectory features, this thesis improves a recently introduced approach that makes use of higher-level features of intentionality. Individuals in a scene are modelled as intentional agents instead of simply objects. Unusual behaviour detection then becomes a task of determining whether an agent's trajectory is explicable in terms of learned spatial goals. The proposed method extends the original goal-based approach in three ways: first, the spatial scene structure is learned in a training phase; second, a region transition model is learned to describe normal movement patterns between spatial regions; and third, classification of trajectories in progress is performed in a probabilistic framework using particle filtering. Experimental validation on three published third-party datasets demonstrates the validity of the proposed approach.

Increased demand for animal disease surveillance information has led to the development and refinement of methodologies for qualitative and quantitative surveillance system evaluations to maximize efficiency and efficaciousness. The impetus for this surveillance evaluation project was chronic wasting disease (CWD) and the objectives were to apply both qualitative and quantitative methodologies to examine the components of CWD surveillance in Saskatchewan.<p> A retrospective review of deer pathology and hunter-harvest submissions in Saskatchewan was conducted through the Canadian Cooperative Wildlife Health Centre. Qualitative evaluation methods outlined by Klauke et al (1988) were used and included key stakeholder interviews. A quantitative evaluation, with specific focus on disease detection, was conducted to examine system sensitivity, confidence of disease freedom and to compare system components using methods described by Martin et al (2007). The analysis was conducted using a scenario tree and Monte Carlo simulation.<p> Sampling rates of dead and clinically ill deer were low with a high degree of variability by season, year, location and nature of submissions. Ultimately, variability of submission patterns likely affected when and where diseases were detected. Poor data quality reduced the amount of available data for analysis but quality dramatically improved over time.<p> The surveillance evaluation demonstrated that the current surveillance system places more emphasis on monitoring trends in CWD-positive areas, at the expense of early detection. This is explained mostly by the coupling of disease control efforts and surveillance, in that harvests are heavily focused in CWD-positive areas. The system is not sufficient to detect disease in new areas where the disease prevalence is low, primarily due to low submission rates.<p> The quantitative evaluation found that overall sensitivity of the surveillance system and confidence of disease freedom was highly dependent on detection prevalence and the ongoing risk of disease introduction. Surveillance in the eastern part of Saskatchewan was not adequate from 1997-2006 to detect CWD at 0.5-1% prevalence. However, if risk of CWD introduction over this time period was assumed to be low, it can be concluded that the prevalence in this region was not 5% or higher.<p> A detection goal of 0.5-1% prevalence is an ambitious surveillance goal, especially in areas where the risk of disease introduction is high. The use of more targeted surveillance strategies should be further explored to help better meet surveillance these surveillance objectives.

The purpose of this study is to better understand the ways in which scientific discourse contributes to the individualization and moralization of obesity, through reality television. Popular reality television programs emphasize the importance of lifestyle to health and wellness, often focusing on participant weight loss. Within this research, I describe the ways in which the obesity epidemic is approached in popular reality television, specifically in NBCs The Biggest Loser, and identify how the discourse of obesity is tied to issues of individualization, surveillance, and morality. Specifically, I undertake a laboratory study of The Biggest Loser to illustrate how this methodology can be extended from the traditional laboratory into a space of science that has no formal walls. With a focus on the seventh season of The Biggest Loser, I argue that the program is based on a human experiment that illustrates the interconnectedness of science and society, while perpetuating individualized and moralized obesity discourse. By conducting a laboratory study of a popular television program, I offer a new way to address obesity discourse

This thesis proposes a merging mechanism for multiple video surveillances in TCP networks. Merging video streams not only can benefit network administration but also reduce the waste of bandwidth. In this thesis, we design a Video-Merging Gateway (VMG) between cameras and control center to merge two video streams transmitted from cameras and received by control center. In the merging mechanism, we develop two modes: Interleave and Overlay. Interleave mode includes two operation types: Single Frame and Proportional. The former merges video streams by interleaving frames one by one from two cameras, and the latter merges video streams according to an FPS (frame per second) ratio between two cameras. Overlay mode vertically displays two video streams in separate frames on the web browser. We implement VMG on a Linux platform. In the interleave mode, we recalculate both the sequence number and the Ack number of a video packet, and create Ack packet for dropped frames while merging two TCP video streams. In the overlay mode, we modify the decoding messages in the frames and separate data between two video streams to avoid decoding errors. Finally, we analyze the complexity of merging algorithms. By carefully determining the timing for responding the created Ack based on Retransmission Time Out (RTO), packet retransmition can be avoided. In addition, we found out that the number of instructions to execute the algorithm is increased by multiple integers along with the picture sizes under interleave mode. As for overlay mode, the number of instructions is increased linearly along with the payload length and the total amount of data and Ack packets.

Constructing and maintaining a formation is critical in applications of cooperative control of multi-agent systems. In this research we address the formation control problem of generating a formation for a group of nonholonomic mobile agents. The formation control scheme proposed in this work is based on a fusion of leader-follower and virtual reference approaches. This scheme gives a formation constraint representation that is independent of the number of agents in the formation and the resulting control algorithm is scalable. One of the important desired features in controller design is that the formation errors defined by formation constraints should be stabilized globally and exponentially by the controller. The proposed controller is based on feedback linearization, and formation errors are shown to be globally exponentially stable in the sense of Lyapunov. Since formation errors are stabilized globally, the proposed controller is applicable to both formation keeping and formation construction problems. As a possible application, the proposed algorithm is implemented in a cooperative ground moving target surveillance scenario. The proposed algorithm enables the determination of the minimal number of agents required for surveillance of a moving target. The number of agents returned by this scheme is not optimal and hence is a conservative solution. However, this is justified by the computational savings the scheme offers.

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Reproduction de : Thèse d'exercice : Médecine : Nancy 1 : 2003. / Titre provenant de l'écran-titre.

Thesis (M.A. in Security Studies (Defense Decision Making and Planning))--Naval Postgraduate School, December 2009. / Thesis Advisor(s): Dahl, Erik. Second Reader: Roberts, Nancy. "December 2009." Description based on title screen as viewed on January 28, 2010. Author(s) subject terms: Persistent surveillance. Includes bibliographical references (p. 61-66). Also available in print.