Long Range Automated Persistent Surveillance

This dissertation addresses long range automated persistent surveillance with focus on three topics: sensor planning, size preserving tracking, and high magnification imaging. field of view should be reserved so that camera handoff can be executed successfully before the object of interest becomes unidentifiable or untraceable. We design a sensor planning algorithm that not only maximizes coverage but also ensures uniform and sufficient overlapped camera’s field of view for an optimal handoff success rate. This algorithm works for environments with multiple dynamic targets using different types of cameras. Significantly improved handoff success rates are illustrated via experiments using floor plans of various scales. Size preserving tracking automatically adjusts the camera’s zoom for a consistent view of the object of interest. Target scale estimation is carried out based on the paraperspective projection model which compensates for the center offset and considers system latency and tracking errors. A computationally efficient foreground segmentation strategy, 3D affine shapes, is proposed. The 3D affine shapes feature direct and real-time implementation and improved flexibility in accommodating the target’s 3D motion, including off-plane rotations. The effectiveness of the scale estimation and foreground segmentation algorithms is validated via both offline and real-time tracking of pedestrians at various resolution levels. Face image quality assessment and enhancement compensate for the performance degradations in face recognition rates caused by high system magnifications and long observation distances. A class of adaptive sharpness measures is proposed to evaluate and predict this degradation. A wavelet based enhancement algorithm with automated frame selection is developed and proves efficient by a considerably elevated face recognition rate for severely blurred long range face images

Dynamic Reconfiguration in Camera Networks: A Short Survey

There is a clear trend in camera networks towards enhanced functionality and flexibility, and a fixed static deployment is typically not sufficient to fulfill these increased requirements. Dynamic network reconfiguration helps to optimize the network performance to the currently required specific tasks while considering the available resources. Although several reconfiguration methods have been recently proposed, e.g., for maximizing the global scene coverage or maximizing the image quality of specific targets, there is a lack of a general framework highlighting the key components shared by all these systems. In this paper we propose a reference framework for network reconfiguration and present a short survey of some of the most relevant state-of-the-art works in this field, showing how they can be reformulated in our framework. Finally we discuss the main open research challenges in camera network reconfiguration

Market_based Framework for Mobile Surveillance Systems

The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given Area Of Interest (AOI). The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This thesis proposes a market-based framework that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target-tracking are studied using the proposed framework as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively

Simulation-based optimization for the placement of surveillance cameras in buildings using BIM

Many companies and organizations highlighted the importance of developing various security monitoring systems for the purpose of protecting their assets against any undesirable events. The process of installing surveillance cameras inside buildings is complex and costly. One of the most important issues that can affect the cost of surveillance cameras in buildings is finding the best placement of cameras. Individuals who are responsible for the camera installation are facing great challenges due to the large number of variables related to this problem. Finding effective scientific methods to address this problem can lead to increasing the efficiency of the camera placement through maximizing the coverage and minimizing the cost. Furthermore, available methods did not take into consideration the impact of different elements (e.g. the HVAC system) that can affect the camera placement. Building Information Modeling (BIM) is becoming an indispensable process for the Architecture, Engineering and Construction (AEC) industry. In terms of security management, BIM technology can improve the performance of security systems during the design phase because of its ability to identify various elements that surround the 3D surveillance cameras in the form of geometrical and non-geometrical entities. iv The objectives of this research are: (1) to develop a method that can help in calculating the coverage of surveillance cameras inside buildings; (2) to investigate the impact of the building elements on the camera configurations, parameters and coverage using BIM; (3) to develop a method that can find the near-optimum types, number and placement of fixed cameras inside a building; and (4) to develop a method that can find the near-optimum placement and movement plan of a Pan-Tilt-Zoom (PTZ) camera inside a building. A method is developed to calculate the camera coverage inside buildings using BIM and a game engine for the purpose of automating the calculation process and achieving accurate results. This method includes a sensitivity analysis for evaluating the suitable cell size in order to cover the monitored area. Also, the research proposes a novel method using BIM, which provides a new opportunity to better optimize the number and locations of cameras by exploiting the rich information available in the model. The near-optimum results aim to maximize the cameras’ coverages and to minimize their costs. BIM is used to define the input of the optimization process and to visualize the results. The method uses Genetic Algorithm (GA) to solve the optimization problem. Finally, the research addresses the placement problem for a PTZ camera. PTZ cameras are used as an addition to fixed cameras in order to ensure the detection of dynamic activities. The research extends the previous method to optimize the placement and movement plan of a PTZ camera inside a building. Several case studies are used to demonstrate the applicability of the proposed methods. The proposed methods can help individuals who are responsible of the camera installation to efficiently determin

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Quality-of-Information Aware Sensing Node Characterisation for Optimised Energy Consumption in Visual Sensor Networks

Energy consumption is one of the primary concerns in a resource constrained visual sensor network (VSN) with wireless transceiving capability. The existing VSN design solutions under particular resource constrained scenarios are application-specific, whereas the degree of sensitivity of the resource constraints varies from one application to another. This limits the implementation of the existing energy efficient solutions within a VSN node, which may be considered to be a part of a heterogeneous network. This thesis aims to resolve the energy consumption issues faced within VSNs because of their resource constrained nature by proposing energy efficient solutions for sensing nodes characterisation. The heterogeneity of image capture and processing within a VSN can be adaptively reflected with a dynamic field-of-view (FoV) realisation. This is expected to allow the implementation of a generalised energy efficient solution that will adapt with the heterogeneity of the network. In this thesis, a FoV characterisation framework is proposed, which can assist design engineers during the pre-deployment phase in developing energy efficient VSNs. The proposed FoV characterisation framework provides efficient solutions for: 1) selecting suitable sensing range; 2) maximising spatial coverage; 3) minimising the number of required nodes; and 4) adaptive task classification. The task classification scheme proposed in this thesis exploits heterogeneity of the network and leads to an optimal distribution of tasks between visual sensing nodes. Soft decision criteria is exploited, and it is observed that for a given detection reliability, the proposed FoV characterisation framework provides energy efficient solutions which can be implemented within heterogeneous networks. In the post-deployment phase, the energy efficiency of a VSN for a given level of reliability can be enhanced by reconfiguring its nodes dynamically to achieve optimal configurations. Considering the dynamic realisation of quality-of-information (QoI), a strategy is devised for selecting suitable configurations of visual sensing nodes to reduce redundant visual content prior to transmission without sacrificing the expected information retrieval reliability. By incorporating QoI awareness using peak signal-to-noise ratio-based representative metric, the distributed nature of the proposed self-reconfiguration scheme accelerates the decision making process. This thesis also proposes a unified framework for node classification and dynamic self-reconfiguration in VSNs. For a given application, the unified framework provides a feasible solution to classify and reconfigure visual sensing nodes based on their FoV by exploiting the heterogeneity of targeted QoI within the sensing region. From the results, it is observed that for the second degree of heterogeneity in targeted QoI, the unified framework outperforms its existing counterparts and results in up to 72% energy savings with as low as 94% reliability. Within the context of resource constrained VSNs, the substantial energy savings achieved by the proposed unified framework can lead to network lifetime enhancement. Moreover, the reliability analysis demonstrates suitability of the unified framework for applications that need a desired level of QoI

Technical Workshop: Advanced Helicopter Cockpit Design

Information processing demands on both civilian and military aircrews have increased enormously as rotorcraft have come to be used for adverse weather, day/night, and remote area missions. Applied psychology, engineering, or operational research for future helicopter cockpit design criteria were identified. Three areas were addressed: (1) operational requirements, (2) advanced avionics, and (3) man-system integration

Space Construction Automated Fabrication Experiment Definition Study (SCAFEDS), part 3. Volume 3: Requirements

The performance, design and verification requirements for the space Construction Automated Fabrication Experiment (SCAFE) are defined. The SCAFE program defines, develops, and demonstrates the techniques, processes, and equipment required for the automatic fabrication of structural elements in space and for the assembly of such elements into a large, lightweight structure. The program defines a large structural platform to be constructed in orbit using the space shuttle as a launch vehicle and construction base

Design, Modelling and Analysis of Satcoms for UAV operations

Η ανάγκη για άμεση συνεισφορά, απόκριση και ακρίβεια των αποτελεσμάτων οδήγησε στην είσοδο των drones και ιδιαίτερα των μη επανδρωμένων εναέριων οχημάτων (UAV) ως νέα τεχνολογικά οχήματα. Ωστόσο, η ενσωμάτωση ενός τόσο κολοσσιαίου τεχνολογικού αποκτήματος δεν είναι καθόλου εύκολη υπόθεση. Πολλές απαιτήσεις εμφανίζονται σε διάφορους τομείς όπως τηλεπικοινωνίες, προβλήματα ωφέλιμου φορτίου που πρέπει να φέρει το UAV και σχέδια λειτουργίας, απαιτήσεις που πρέπει να πληρούνται για την αποφυγή προβλημάτων ασφάλειας, αποφυγή σύγκρουσης, ασταθείς συνδέσεις και άλλα. Σκοπός της παρούσας διπλωματικής εργασίας είναι να μελετήσει όσο το δυνατόν καλύτερα και αποτελεσματικότερα τη συμβολή των δορυφορικών επικοινωνιών στην επίτευξη αξιόπιστων και ανθεκτικών επιχειρήσεων Μη Επανδρωμένων Αεροσκαφών (UAV). Θα παρουσιαστεί μια ανάλυση τριών επιπέδων που θα αφορά τον Σχεδιασμό, τη Μοντελοποίηση και την Ανάλυση δορυφορικών επικοινωνιών σε συνδυασμό με λειτουργίες UAV με τρόπο που η αποτελεσματικότητα της ζεύξης θα είναι μέγιστη εφικτή. Σε τελική ανάλυση, θα πραγματοποιηθεί ένα πείραμα που θα συζητηθούν τα αποτελέσματα και οι παράμετροι που χρησιμοποιούνται προκειμένου να υπολογιστεί η αποτελεσματικότητα του προϋπολογισμού των ζεύξεων. Είναι σημαντικό να γνωρίζουμε ότι οι κυψελοειδείς επικοινωνίες έχουν παίξει μέχρι στιγμής τον πιο σημαντικό και ακριβή ρόλο τόσο στις επίγειες όσο και στις αεροπορικές επικοινωνίες. Αυτό πρόκειται να αλλάξει καθώς οι δορυφόροι υπόσχονται χαρακτηριστικά που δεν μπορούν να ανταγωνιστούν τα επίγεια δίκτυα, με αποτέλεσμα την ενοποίηση των UAV με τις δορυφορικές επικοινωνίες. Ωστόσο, τα πράγματα είναι ασαφή και οι κίνδυνοι που ενέχουν είτε από την άποψη των προσωπικών δεδομένων είτε από την ασφάλεια και την υγεία μπορούν να λειτουργήσουν ως εμπόδιο στην ανάπτυξη και την αναβάθμιση των επικοινωνιών.The need for immediate contribution, response, and accuracy of results has led to the entry of drones and especially Unmanned Aerial Vehicles (UAVs) as new technological vehicles. However, the integration of such a colossal technological acquisition is by no means an easy task. Many requirements appear in various areas such as telecommunications, payload problems that the UAV must carry, and operations plans, requirements that must be met to avoid safety issues, collision avoidance, unstable connections, and so more. The purpose of this thesis is to study as best as possible and most effectively the contribution of satellite communications to achieve reliable and durable Unmanned Aerial Vehicles (UAVs) operations. A three-level analysis will be presented which will concern the Design, Modeling, and Analysis of satellite communications in combination with UAV operations in a way where efficiency of the link will be maximum. After all, an experiment will take place that results and parameters used will be discussed in order to compute the efficiency of the link budget. It is important to know that cellular communications have so far played the most important and accurate role in both terrestrial and air communications. This is about to change as satellites promise features that cannot compete with terrestrial networks, resulting in the integration of UAVs with satellite communications. However, things are unclear, and the risks posed either from the point of view of personal data or from safety and health can act as an obstacle in developing and upgrading communications