CCTV as a Smart Sensor Network

With the emergence of so-called 'smart CCTV' being able to recognise the precursors for disorder and civil disobedience, we present a preliminary study into using available CCTV networks augmented with big social media datasets. We examine the existing CCTV infrastructure in the UK, and use an agent-based simulation to model interactions between people based on friendship networks and features derived from their social media usage, proposing a novel algorithm for detection of psychopathy. Finally, we explore the frequency of crimes occurring within CCTV viewsheds using available UK police crime datasets to illustrate the current limitations of the CCTV infrastructure, as well as the potential ramifications of the stealthy emergence of CCTV networks as the fifth utility in smart cities

Design for A Remote Smart Home Monitor Using the Internet of Things (IoT)

Designing a Remote Smart Home Monitor Based on the Internet of Things (IoT) using the NodeMCU ESP32 microcontroller as a wifi network provider and also utilizing Firebase Technology as a data storage medium. This remote smart home monitor with the Internet of Things concept is safe because only people who have certain access can control home appliances such as turning on lights, fans, opening doors, filling water in the bath, preventing theft, in Remote Smart Home Monitors also uses CCTV cameras that utilize special applications, with the selection of these communication technologies efficiently and also saving power in controlling and monitoring from smart home remotely via smartphones. Test results control data can function properly when the switch control is activated then the lights, fans, doors will automatically turn on. Test results PIR sensor can detect movement or when the door is open and the buzzer will sound sending information on the android application. Test results, the ultrasonic sensor can work when the sensor reads the water distance >15 cm then the pump will work to fill the water and when the sensor distance reads the distance <2 cm then the pump will stop to fill the water.Designing a Remote Smart Home Monitor Based on the Internet of Things (IoT) using the NodeMCU ESP32 microcontroller as a wifi network provider and also utilizing Firebase Technology as a data storage medium. This remote smart home monitor with the Internet of Things concept is safe because only people who have certain access can control home appliances such as turning on lights, fans, opening doors, filling water in the bath, preventing theft, in Remote Smart Home Monitors also uses CCTV cameras that utilize special applications, with the selection of these communication technologies efficiently and also saving power in controlling and monitoring from smart home remotely via smartphones. Test results control data can function properly when the switch control is activated then the lights, fans, doors will automatically turn on. Test results PIR sensor can detect movement or when the door is open and the buzzer will sound sending information on the android application. Test results, the ultrasonic sensor can work when the sensor reads the water distance >15 cm then the pump will work to fill the water and when the sensor distance reads the distance <2 cm then the pump will stop to fill the water

Video analysis of events within chemical sensor networks

This paper describes how we deploy video surveillance techniques to monitor the activities within a sensor network in order to detect environmental events. This approach combines video and sensor networks in a completely different way to what would be considered the norm. Sensor networks consist of a collection of autonomous, self-powered nodes which sample their environment to detect anything from chemical pollutants to atypical sound patterns which they report through an ad hoc network. In order to reduce power consumption nodes have the capacity to communicate with neighbouring nodes only. Typically these communications are via radio waves but in this paper the sensor nodes communicate to a base station through patterns emitted by LEDs and captured by a video camera. The LEDs are chemically coated to react to their environment and on doing so emit light which is then picked up by video analysis. There are several advantages to this approach and to demonstrate we have constructed a controlled test environment. In this paper we introduce and briefly describe this environment and the sensor nodes but focus mainly on the video capture, image processing and data visualisation techniques used to indicate these events to a user monitoring the network

On the Role of Primary and Secondary Assets in Adaptive Security: An Application in Smart Grids

peer-reviewedAdaptive security aims to protect valuable assets managed by a system, by applying a varying set of security controls. Engineering adaptive security is not an easy task. A set of effective security countermeasures should be identified. These countermeasures should not only be applied to (primary) assets that customers desire to protect, but also to other (secondary) assets that can be exploited by attackers to harm the primary assets. Another challenge arises when assets vary dynamically at runtime. To accommodate these variabilities, it is necessary to monitor changes in assets, and apply the most appropriate countermeasures at runtime. The paper provides three main contributions for engineering adaptive security. First, it proposes a modeling notation to represent primary and secondary assets, along with their variability. Second, it describes how to use the extended models in engineering security requirements and designing required monitoring functions. Third, the paper illustrates our approach through a set of adaptive security scenarios in the customer domain of a smart grid. We suggest that modeling secondary assets aids the deployment of countermeasures, and, in combination with a representation of assets variability, facilitates the design of monitoring function

Sensor node localisation using a stereo camera rig

In this paper, we use stereo vision processing techniques to detect and localise sensors used for monitoring simulated environmental events within an experimental sensor network testbed. Our sensor nodes communicate to the camera through patterns emitted by light emitting diodes (LEDs). Ultimately, we envisage the use of very low-cost, low-power, compact microcontroller-based sensing nodes that employ LED communication rather than power hungry RF to transmit data that is gathered via existing CCTV infrastructure. To facilitate our research, we have constructed a controlled environment where nodes and cameras can be deployed and potentially hazardous chemical or physical plumes can be introduced to simulate environmental pollution events in a controlled manner. In this paper we show how 3D spatial localisation of sensors becomes a straightforward task when a stereo camera rig is used rather than a more usual 2D CCTV camera

Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The safety, mobility, environmental and economic benefits of Connected and Autonomous Vehicles (CAVs) are potentially dramatic. However, realization of these benefits largely hinges on the timely upgrading of the existing transportation system. CAVs must be enabled to send and receive data to and from other vehicles and drivers (V2V communication) and to and from infrastructure (V2I communication). Further, infrastructure and the transportation agencies that manage it must be able to collect, process, distribute and archive these data quickly, reliably, and securely. This paper focuses on current digital roadway infrastructure initiatives and highlights the importance of including digital infrastructure investment alongside more traditional infrastructure investment to keep up with the auto industry's push towards this real time communication and data processing capability. Agencies responsible for transportation infrastructure construction and management must collaborate, establishing national and international platforms to guide the planning, deployment and management of digital infrastructure in their jurisdictions. This will help create standardized interoperable national and international systems so that CAV technology is not deployed in a haphazard and uncoordinated manner

Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration

There is increasing reliance on video surveillance systems for systematic derivation, analysis and interpretation of the data needed for predicting, planning, evaluating and implementing public safety. This is evident from the massive number of surveillance cameras deployed across public locations. For example, in July 2013, the British Security Industry Association (BSIA) reported that over 4 million CCTV cameras had been installed in Britain alone. The BSIA also reveal that only 1.5% of these are state owned. In this paper, we propose a framework that allows access to data from privately owned cameras, with the aim of increasing the efficiency and accuracy of public safety planning, security activities, and decision support systems that are based on video integrated surveillance systems. The accuracy of results obtained from government-owned public safety infrastructure would improve greatly if privately owned surveillance systems ‘expose’ relevant video-generated metadata events, such as triggered alerts and also permit query of a metadata repository. Subsequently, a police officer, for example, with an appropriate level of system permission can query unified video systems across a large geographical area such as a city or a country to predict the location of an interesting entity, such as a pedestrian or a vehicle. This becomes possible with our proposed novel hierarchical architecture, the Fused Video Surveillance Architecture (FVSA). At the high level, FVSA comprises of a hardware framework that is supported by a multi-layer abstraction software interface. It presents video surveillance systems as an adapted computational grid of intelligent services, which is integration-enabled to communicate with other compatible systems in the Internet of Things (IoT)