Wireless Sensor Networks and Real-Time Locating Systems to Fight against Maritime Piracy

There is a wide range of military and civil applications where Wireless Sensor Networks (WSNs) and Multi-Agent Systems (MASs) can be used for providing context-awareness for troops and special corps. On the one hand, WSNs comprise an ideal technology to develop Real-Time Locating Systems (RTLSs) aimed at indoor environments, where existing global navigation satellite systems do not work properly. On the other hand, agent-based architectures allow building autonomous and robust systems that are capable of working on highly dynamic scenarios. This paper presents two piracy scenarios where the n-Core platform can be applied. n-Core is a hardware and software platform intended for developing and deploying easily and quickly a wide variety of WSNs applications based on the ZigBee standard. In the first scenario a RTLS is deployed to support boarding and rescue operations. In the second scenario a multi-agent system is proposed to detect the unloading of illegal traffic of merchandise at ports

Analysis of GPS and UWB positioning system for athlete tracking

In recent years, wearable performance monitoring systems have become increasingly popular in competitive sports. Wearable devices can provide vital information including distance covered, velocity, change of direction, and acceleration, which can be used to improve athlete performance and prevent injuries. Tracking technology that monitors the movement of an athlete is an important element of sport wearable devices. For tracking, the cheapest option is to use global positioning system (GPS) data however, their large margins of error are a major concern in many sports. Consequently, indoor positioning systems (IPS) have become popular in sports in recent years where the ultra-wideband (UWB) positioning sensor is now being used for tracking. IPS promises much higher accuracy, but unlike GPS, it requires a longer set-up time and its costs are significantly more. In this research, we investigate the suitability of the UWB-based localisation technique for wearable sports performance monitoring systems. We implemented a hardware set-up for both positioning sensors, UWB and the GPS-based (both 10 Hz and 1 Hz) localisation systems, and then monitored their accuracy in 2D and 3D side-by-side for the sport of tennis. Our gathered data shows a major drawback in the UWB-based localisation system. To address this major drawback we introduce an artificial intelligent model, which shows some promising results

Implementing a real-time locating system based on wireless sensor networks and artificial neural networks to mitigate the multipath effect

Wireless Sensor Networks comprise an ideal technology to develop Real-Time Locating Systems (RTLSs) aimed at indoor environments, where existing global navigation satellite systems do not work correctly due to the blockage of the satellite signals. In this regard, one of the main challenges is to deal with the problems that arise from the effects of the propagation of radio frequency waves, such as multipath. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the multipath effect by using Multi-Layer Perceptron Artificial Neural Networks. The model is used to implement a novel indoor Real-Time Locating System based on Wireless Sensor Networks

Automatic Calibration of Ultra Wide Band Tracking Systems Using A Mobile Robot: A Person Localization Case-study

Ultra Wide Band (UWB) is an emerging technology in the field of indoor localization, mainly due to its high performances in indoor scenarios and relatively easy deployment. However, in complex indoor environments, its positioning accuracy may drastically decrease due to biases introduced when emitters and receivers operate in Non Line-of-Sight (NLOS) conditions. This undesired phenomenon can be attenuated by creating, a priori, a map of the measurement error in the environment, that can be exploited at a later stage by a localization algorithm. In this paper, the error map is the result of a calibration process, which consists of collecting several measurements of the localization system at different locations in the environment. This work proposes the leveraging of mobile robots in order to automatize the calibration process with the ultimate purpose of improving UWB-based people localization in a realistic indoor environment. The whole process exploits existing algorithms in the field of robot localization conveniently adapted in order to address our use case and technology. Experiments in real environments of incrementally increasing complexity show how the average localization accuracy can be improved up to 50% by adopting this method

An overview of data fusion techniques for internet of things enabled physical activity recognition and measure

Due to importantly beneficial effects on physical and mental health and strong association with many rehabilitation programs, Physical Activity Recognition and Measure (PARM) has been widely recognised as a key paradigm for a variety of smart healthcare applications. Traditional methods for PARM relies on designing and utilising Data fusion or machine learning techniques in processing ambient and wearable sensing data for classifying types of physical activity and removing their uncertainties. Yet they mostly focus on controlled environments with the aim of increasing types of identifiable activity subjects, improved recognition accuracy and measure robustness. The emergence of the Internet of Things (IoT) enabling technology is transferring PARM studies to an open and dynamic uncontrolled ecosystem by connecting heterogeneous cost-effective wearable devices and mobile apps and various groups of users. Little is currently known about whether traditional Data fusion techniques can tackle new challenges of IoT environments and how to effectively harness and improve these technologies. In an effort to understand potential use and opportunities of Data fusion techniques in IoT enabled PARM applications, this paper will give a systematic review, critically examining PARM studies from a perspective of a novel 3D dynamic IoT based physical activity collection and validation model. It summarized traditional state-of-the-art data fusion techniques from three plane domains in the 3D dynamic IoT model: devices, persons and timeline. The paper goes on to identify some new research trends and challenges of data fusion techniques in the IoT enabled PARM studies, and discusses some key enabling techniques for tackling them

Web services approach for ambient assisted living in mobile environments

Web services appeared as a promising technology for Web environments independent of technologies, services, and applications. First, a performance comparison study between the two most used Web service architectures, SOAP and REST, is presented, considering messages exchange between clients and a server. Based on this study, the REST architecture was chosen to deploy the system because it gets better results compared to SOAP architecture. Currently, there are some issues related with this approach that should be studied. For instance, if massive quantities of data are sent to databases it can influence significantly the performance of the whole system. The Advanced Message Queuing Protocol (AMPQ) appears as a promising solution to address this problem. Then, in order to evaluate the performance of this approach, this work presents a performance evaluation and a comparison study of RESTful Web services and the AMQP Protocol considering exchanging messages between clients and a server. The study is based on the averaged exchanged messages for a certain period of time. It was observed and concluded that, for large quantities of messages exchange, the best results comes from the Advanced Message Queuing Protocol. Message Queuing Telemetry Transport (MQTT) was addressed in this work because it is a similar protocol to AMQP but it can be used by mobile devices with a processing capacity smallest unlike the AMQP that needs greater processing capacity. These studies are performed in the context of Ambient Assisted Living environments, since the work was applied to this topic in order to experiment the effectiveness and evaluate the performance of these protocols in this scenario

Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review.

Due to importantly beneficial effects on physical and mental health and strong association with many rehabilitation programs, Physical Activity Recognition and Monitoring (PARM) have been considered as a key paradigm for smart healthcare. Traditional methods for PARM focus on controlled environments with the aim of increasing the types of identifiable activity subjects complete and improving recognition accuracy and system robustness by means of novel body-worn sensors or advanced learning algorithms. The emergence of the Internet of Things (IoT) enabling technology is transferring PARM studies to open and connected uncontrolled environments by connecting heterogeneous cost-effective wearable devices and mobile apps. Little is currently known about whether traditional PARM technologies can tackle the new challenges of IoT environments and how to effectively harness and improve these technologies. In an effort to understand the use of IoT technologies in PARM studies, this paper will give a systematic review, critically examining PARM studies from a typical IoT layer-based perspective. It will firstly summarize the state-of-the-art in traditional PARM methodologies as used in the healthcare domain, including sensory, feature extraction and recognition techniques. The paper goes on to identify some new research trends and challenges of PARM studies in the IoT environments, and discusses some key enabling techniques for tackling them. Finally, this paper consider some of the successful case studies in the area and look at the possible future industrial applications of PARM in smart healthcare

Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications

Nowadays, the availability of the location information becomes a key factor in today’s communications systems for allowing location based services. In outdoor scenarios, the Mobile Terminal (MT) position is obtained with high accuracy thanks to the Global Positioning System (GPS) or to the standalone cellular systems. However, the main problem of GPS or cellular systems resides in the indoor environment and in scenarios with deep shadowing effect where the satellite or cellular signals are broken. In this paper, we will present a review over different technologies and concepts used to improve indoor localization. Additionally, we will discuss different applications based on different localization approaches. Finally, comprehensive challenges in terms of accuracy, cost, complexity, security, scalability, etc. are presente

Design and Implementation of a Low‐Power Wireless Respiration Monitoring Sensor

Wireless devices for monitoring of respiration activities can play a major role in advancing modern home-based health care applications. Existing methods for respiration monitoring require special algorithms and high precision filters to eliminate noise and other motion artifacts. These necessitate additional power consuming circuitry for further signal conditioning. This dissertation is particularly focused on a novel approach of respiration monitoring based on a PVDF-based pyroelectric transducer. Low-power, low-noise, and fully integrated charge amplifiers are designed to serve as the front-end amplifier of the sensor to efficiently convert the charge generated by the transducer into a proportional voltage signal. To transmit the respiration data wirelessly, a lowpower transmitter design is crucial. This energy constraint motivates the exploration of the design of a duty-cycled transmitter, where the radio is designed to be turned off most of the time and turned on only for a short duration of time. Due to its inherent duty-cycled nature, impulse radio ultra-wideband (IR-UWB) transmitter is an ideal candidate for the implementation of a duty-cycled radio. To achieve better energy efficiency and longer battery lifetime a low-power low-complexity OOK (on-off keying) based impulse radio ultra-wideband (IR-UWB) transmitter is designed and implemented using standard CMOS process. Initial simulation and test results exhibit a promising advancement towards the development of an energy-efficient wireless sensor for monitoring of respiration activities

Improving Indoor Security Surveillance by Fusing Data from BIM, UWB and Video

Indoor physical security, as a perpetual and multi-layered phenomenon, is a time-intensive and labor-consuming task. Various technologies have been leveraged to develop automatic access control, intrusion detection, or video monitoring systems. Video surveillance has been significantly enhanced by the advent of Pan-Tilt-Zoom (PTZ) cameras and advanced video processing, which together enable effective monitoring and recording. The development of ubiquitous object identification and tracking technologies provides the opportunity to accomplish automatic access control and tracking. Intrusion detection has also become possible through deploying networks of motion sensors for alerting about abnormal behaviors. However, each of the above-mentioned technologies has its own limitations. This thesis presents a fully automated indoor security solution that leverages an Ultra-wideband (UWB) Real-Time Locating System (RTLS), PTZ surveillance cameras and a Building Information Model (BIM) as three sources of environmental data. Providing authorized persons with UWB tags, unauthorized intruders are distinguished as the mismatch observed between the detected tag owners and the persons detected in the video, and intrusion alert is generated. PTZ cameras allow for wide-area monitoring and motion-based recording. Furthermore, the BIM is used for space modeling and mapping the locations of intruders in the building. Fusing UWB tracking, video and spatial data can automate the entire security procedure from access control to intrusion alerting and behavior monitoring. Other benefits of the proposed method include more complex query processing and interoperability with other BIM-based solutions. A prototype system is implemented that demonstrates the feasibility of the proposed method