Duarte Raposo

A scalable localization system for critical controlled wireless sensor networks

Determining the positions of unknown position nodes, especially mobile nodes in a wireless sensor network (WSN), is critical for many applications. It helps to identify the location of the collected data and of the node carrier such as a worker, patient or vehicle. This information is often critical on supporting the right (time) decisions. This paper presents a scalable localization system targeting Controlled WSNs for critical industrial environments. Multiple positioning methods were implemented and evaluated using real testbeds setting up in both laboratory and industrial environments. The measurement used in our localization system is Received Signal Strength Indicator (RSSI). Although it is unstable and with high variance, the experimental results show that pattern matching based methods such as k-nearest neighbors, probability-based (Bayesian Theorem) and Kalman filter over probability-based produce an acceptable accuracy that is sufficient for many applications. In particular, the average distance error of 3.37m can be achieved with 50th and 80th percentile distance errors of 2 and 5.35m respectively. In addition, by carefully designing the positions of beacons it is possible to obtain the average distance error about 2.23m and 50th and 80th percentile distance errors of 0.46 and less than 4.4m respectively.

A Taxonomy of Faults for Wireless Sensor Networks

Over the last decade, Wireless Sensor Networks (WSN) went from being a promising technology to the main enabler of countless Internet of Things applications in all types of areas. In industry, WSNs are now used for monitoring and controlling industrial processes, with the benefits of low installation costs, self-organization, self-configuration, and added functionality. Nevertheless, despite the fact that base WSN technologies are quite stable and subject to standardization, they have kept one of their main characteristics: fault-proneness. As a result, in recent years considerable effort has been made in order to provide mechanisms that increase the availability, reliability and maintainability of this type of networks. In this context, a whole range of techniques such as fault detection, fault identification and fault diagnosis used in other research fields are now being applied to WSNs. Unfortunately, this has not led to a consistent, comprehensive WSN fault taxonomy that can be used to characterize and/or classify faults. Neglecting the importance of WSN fault characterization (e.g., when using supervised algorithms for anomaly detection) may lead to bad classifiers and, consequently, bad fault handling procedures and/or tools. In this paper, we start by reviewing base fault management concepts and techniques that can be applied to WSNs. We then proceed to propose and present a comprehensive WSN fault taxonomy that can be used not only in general purpose WSNs but also in Industrial WSNs. Finally, the proposed taxonomy is validated by applying it to an extensive set of faults described in the literature.

A Web Service-based framework model for people-centric sensing applications applied to social networking.

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype.

Happy hour - improving mood with an emotionally aware application

Mobile sensing in Cyber-Physical Systems has been evolving proportionally with smartphones. In fact, we are witnessing a tremendous increase in systems that sense various facets of human beings and their surrounding environments. In particular, the detection of human emotions can lead to emotionally-aware applications that use this information to benefit peoples daily lives. This work presents the implementation of a Human-inthe- loop emotionally-aware Cyber-Physical System that attempts to positively impact its users mood through moderate walking exercise. Data from smartphone sensors, a smartshirts electrocardiogram and weather information from a web API are processed through a machine learning algorithm to infer emotional states. When negative emotions are detected, the application timely suggests walking exercises, while providing real-time information regarding nearby points of interest. This information includes events, background music, attendance, agitation and general mood. In addition, the system also dynamically adapts privacy and networking configurations based on emotions. The sharing of the users location on social networks and the devices networking interfaces are configured according to user-defined rules in order to reduce frustration and provide a better Quality of Experience.

Place-&-Play industrial router addressing potential explosive atmospheres

In general, deployments of Wireless Sensors Networks in industrial rigs face several constrains, especially those concerning power supply of scattered devices: cabling is expensive and takes a long time, and, on the hand, batteries are sensitive to both current peaks and high temperatures, thus requiring periodic replacement. This work presents a low power router which, by gathering energy from a tiny solar panel and storing it in a supercapacitor, addresses the stringent regulations that have to be met to work in potentially explosive atmospheres and, still, keep working continuously so as to serve communication requirements of wireless networks in such harsh environments: evaluation of the energy balance under different harvesting and consumption conditions was carried out, whose results ensure the feasibility of this technology.

Industrial IoT Monitoring: Technologies and Architecture Proposal

Dependability and standardization are essential to the adoption of Wireless Sensor Networks (WSN) in industrial applications. Standards such as ZigBee, WirelessHART, ISA100.11a and WIA-PA are, nowadays, at the basis of the main process-automation technologies. However, despite the success of these standards, management of WSNs is still an open topic, which clearly is an obstacle to dependability. Existing diagnostic tools are mostly application- or problem-specific, and do not support standard-based multi-network monitoring. This paper proposes a WSN monitoring architecture for process-automation technologies that addresses the mentioned limitations. Specifically, the architecture has low impact on sensor node resources, uses network metrics already available in industrial standards, and takes advantage of widely used management standards to share the monitoring information. The proposed architecture was validated through prototyping, and the obtained performance results are presented and discussed in the final part of the paper. In addition to proposing a monitoring architecture, the paper provides an in-depth insight into metrics, techniques, management protocols, and standards applicable to industrial WSNs.

WSNs in FIWARE – Towards the Development of People-Centric Applications

Wireless Sensors Networks (WSNs) form the founding block of the Internet of Things (IoT) Sensing Layer. In IoT scenarios, programmers will make the most of IoT if they focus on the development of context-aware applications rather than managing low-level aspects of the network they run on. To this end, providing harmonized data models eases the development of applications. Focusing on crossbow-micaZ sensors, we present an approach to integrate a heterogeneous WSN platform into FIWARE, towards the development of people-centric applications.

Tech4SocialChange: Technology for All

Universities and other educational institutions are sometimes accused of not being involved in real world problems, focusing more on the scientifically value of the work produced and not on the humanitarian value. A way of encapsulating the second with the first is the main goal of the Tech4SocialChange that is described here. An innovative database/repository of challenges with real impact in the world is created and given access to people with skills and knowledge to tackle them. Also the work made by researches can be stored and used in a project and the researcher gets recognition for it by becoming referenced in that project. A web application has been built as a prototype for this process and can be accessed in www.tech4socialchange.org. It has been planned and developed by a team of students and researchers of the Department of Informatics Engineering of the University of Coimbra and is currently being constantly altered according to feedback received by the testers in the same team. This paper presents an application that aims to help people that face certain challenges every day and motivate those that have the skillset, to tackle these challenges, into doing so.

Achieving Human-Aware Seamless Handoff

Smartphones have spawned a new generation of people-centric sensing applications, where their sensors gather information from users to achieve a wide range of objectives, from fitness monitoring to the urban-wide management of traffic. The connections between devices are of utmost importance for these systems, in fact, switching between the multitude of network interfaces available to smartphones (3G/4G, WiFi) can be beneficial to improve connectivity, the distribution of network traffic and save battery power. Current solutions in the literature for the management of network interfaces are limited in the sense that they only consider either application requirements or the systems status. In this paper, we propose a new model that considers not only these aspects but also the human-context, that is, the users position and activity to intelligently manage which interfaces should be used. To support the switching between different interfaces without interrupting existing connections, we also discuss several handoff techniques. Finally, we present an experimental evaluation of our model based on Multipath TCP.