MakeSense: An IoT Testbed for Social Research of Indoor Activities

There has been increasing interest in deploying IoT devices to study human behaviour in locations such as homes and offices. Such devices can be deployed in a laboratory or `in the wild' in natural environments. The latter allows one to collect behavioural data that is not contaminated by the artificiality of a laboratory experiment. Using IoT devices in ordinary environments also brings the benefits of reduced cost, as compared with lab experiments, and less disturbance to the participants' daily routines which in turn helps with recruiting them into the research. However, in this case, it is essential to have an IoT infrastructure that can be easily and swiftly installed and from which real-time data can be securely and straightforwardly collected. In this paper, we present MakeSense, an IoT testbed that enables real-world experimentation for large scale social research on indoor activities through real-time monitoring and/or situation-aware applications. The testbed features quick setup, flexibility in deployment, the integration of a range of IoT devices, resilience, and scalability. We also present two case studies to demonstrate the use of the testbed, one in homes and one in offices.Comment: 20 pages, 11 figure

Integrated system architecture for decision-making and urban planning in smart cities

Research and development of applications for smart cities are extremely relevant considering the various problems that population growth will bring to large urban centers in the next few years. Although research on cyber-physical systems, cloud computing, embedded devices, sensor and actuator networks, and participatory sensing, among other paradigms, is driving the growth of solutions, there are a lot of challenges that need to be addressed. Based on these observations, in this work, we present an integrated system architecture for decision-making support and urban planning by introducing its building blocks (termed components): sensing/actuation, local processing, communication, cloud platform, and application components. In the sensing/actuation component, we present the major relevant resources for data collection, identification devices, and actuators that can be used in smart city solutions. Sensing/actuation component is followed by the local processing component, which is responsible for processing, decision-making support, and control in local scale. The communication component, as the connection element among all these components, is presented with an emphasis on the open-access metropolitan area network and cellular networks. The cloud platform is the essential component for urban planning and integration with electronic governance legacy systems, and finally, the application component, in which the government administrator and users have access to public management tools, citizen services, and other urban planning resources15

IoT oriented SIEM tools

openNowadays, most devices can connect and communicate data. One example is IoT devices, technological devices that can communicate information gathered from the environment with a high degree of automation, communicating the data through networks. New IoT devices and increasingly reliable and fast wireless networks make it easy to collect large amounts of data with high accuracy. The introduction of these new technologies has created new vulnerabilities in complex systems, allowing an attacker to breach them more easily. Attackers use these devices, which generally lack important protections because they are composed of minimal hardware. Generally, the attackers' goal is to capture data, create malfunctions, steal sensitive and personal information and more. In order to protect and limit the actions of possible attackers, new software has been developed to neutralise or reduce vulnerabilities in a complex system. An example of software that belongs to this category is SIEM which is analysed in this thesis. They make it possible to analyse real-time data and logs to understand the system situation. They give the possibility of creating a history of the information collected by the system, indexing the data allowing efficient and fast analysis. In addition, they make it possible to visualise the collected data in a user-friendly way. The introduction of artificial intelligence has made these tools more precise, allowing the automatic creation of thresholds that generate alerts in critical situations if exceeded. These tools may also be able to autonomously analyse the environment, identify any vulnerability in the system, and respond to certain situations autonomously. In this thesis, SIEM and IoT are combined. The purpose is to evaluate the effectiveness of the tool in protecting a complex system that also consists of IoT devices. Greenhouse sensors are simulated communicating data using the MQTT protocol. DoS attacks are performed in the system and the network status is collected using SIEM. With the use of the SIEM, user-friendly visualisations are made available to the security teams to easily analyse and evaluate the status of the system. In conclusion, the combination of IoT devices and SIEM is effective and easy to implement, thanks in part to the use of the MQTT data protocol. This provides end-users with a tool that allows them to easily detect and resolve vulnerabilities that may be present within a complex system, relating to security, authentication and authorisation. They can also evaluate the information collected by the sensors. Thanks to the low cost of implementation, and ease and intuitiveness of deployment, this combination can also be easily used by end-users without high economic means and in any field, becoming a tool accessible to anyone.Nowadays, most devices can connect and communicate data. One example is IoT devices, technological devices that can communicate information gathered from the environment with a high degree of automation, communicating the data through networks. New IoT devices and increasingly reliable and fast wireless networks make it easy to collect large amounts of data with high accuracy. The introduction of these new technologies has created new vulnerabilities in complex systems, allowing an attacker to breach them more easily. Attackers use these devices, which generally lack important protections because they are composed of minimal hardware. Generally, the attackers' goal is to capture data, create malfunctions, steal sensitive and personal information and more. In order to protect and limit the actions of possible attackers, new software has been developed to neutralise or reduce vulnerabilities in a complex system. An example of software that belongs to this category is SIEM which is analysed in this thesis. They make it possible to analyse real-time data and logs to understand the system situation. They give the possibility of creating a history of the information collected by the system, indexing the data allowing efficient and fast analysis. In addition, they make it possible to visualise the collected data in a user-friendly way. The introduction of artificial intelligence has made these tools more precise, allowing the automatic creation of thresholds that generate alerts in critical situations if exceeded. These tools may also be able to autonomously analyse the environment, identify any vulnerability in the system, and respond to certain situations autonomously. In this thesis, SIEM and IoT are combined. The purpose is to evaluate the effectiveness of the tool in protecting a complex system that also consists of IoT devices. Greenhouse sensors are simulated communicating data using the MQTT protocol. DoS attacks are performed in the system and the network status is collected using SIEM. With the use of the SIEM, user-friendly visualisations are made available to the security teams to easily analyse and evaluate the status of the system. In conclusion, the combination of IoT devices and SIEM is effective and easy to implement, thanks in part to the use of the MQTT data protocol. This provides end-users with a tool that allows them to easily detect and resolve vulnerabilities that may be present within a complex system, relating to security, authentication and authorisation. They can also evaluate the information collected by the sensors. Thanks to the low cost of implementation, and ease and intuitiveness of deployment, this combination can also be easily used by end-users without high economic means and in any field, becoming a tool accessible to anyone

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets

This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade

WikiSensing: A collaborative sensor management system with trust assessment for big data

Big Data for sensor networks and collaborative systems have become ever more important in the digital economy and is a focal point of technological interest while posing many noteworthy challenges. This research addresses some of the challenges in the areas of online collaboration and Big Data for sensor networks. This research demonstrates WikiSensing (www.wikisensing.org), a high performance, heterogeneous, collaborative data cloud for managing and analysis of real-time sensor data. The system is based on the Big Data architecture with comprehensive functionalities for smart city sensor data integration and analysis. The system is fully functional and served as the main data management platform for the 2013 UPLondon Hackathon. This system is unique as it introduced a novel methodology that incorporates online collaboration with sensor data. While there are other platforms available for sensor data management WikiSensing is one of the first platforms that enable online collaboration by providing services to store and query dynamic sensor information without any restriction of the type and format of sensor data. An emerging challenge of collaborative sensor systems is modelling and assessing the trustworthiness of sensors and their measurements. This is with direct relevance to WikiSensing as an open collaborative sensor data management system. Thus if the trustworthiness of the sensor data can be accurately assessed, WikiSensing will be more than just a collaborative data management system for sensor but also a platform that provides information to the users on the validity of its data. Hence this research presents a new generic framework for capturing and analysing sensor trustworthiness considering the different forms of evidence available to the user. It uses an extensible set of metrics that can represent such evidence and use Bayesian analysis to develop a trust classification model. Based on this work there are several publications and others are at the final stage of submission. Further improvement is also planned to make the platform serve as a cloud service accessible to any online user to build up a community of collaborators for smart city research.Open Acces

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Estudi bibliomètric any 2014. Campus del Baix Llobregat: EETAC i ESAB

En el present informe s’analitza la producció científica de les dues escoles del Campus del Baix Llobregat, l’Escola d’Enginyeria de Telecomunicació i Aerospacial de Castelldefels (EETAC) i l’Escola Superior d’Agricultura de Barcelona (ESAB) durant el 2014.Postprint (author’s final draft