An Ambient Agent Model for Monitoring and Analysing Dynamics of Complex Human Behaviour

In ambient intelligent systems, monitoring of a human could consist of more complex tasks than merely identifying whether a certain value of a sensor is above a certain threshold. Instead, such tasks may involve monitoring of complex dynamic interactions between human and environment. In order to enable such more complex types of monitoring, this paper presents a generic agent-based framework. The framework consists of support on various levels of system design, namely: (1) the top level, including the interaction between agents, (2) the agent level, providing support on the design of individual agents, and (3) the level of monitoring complex dynamic behaviour, allowing the specification of the aforementioned complex monitoring properties within the agents. The approach is exemplified by a large case study concerning the assessment of driving behaviour, and is applied to two smaller cases as well (concerning fall detection of elderly, and assistance of naval operations, respectively), which are briefly described. These case studies have illustrated that the presented framework enables developers within ambient intelligence to build systems with more expressiveness regarding their monitoring focus. Moreover, they have shown that the framework is easy to use and applicable in a wide variety of domains. © 2011 - IOS Press and the authors. All rights reserved

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Debonding along the fixed anchor length of a ground anchorage

Peer reviewedPostprin

Ubiquitous sensorization for multimodal assessment of driving patterns

Sustainability issues and sustainable behaviours are becoming concerns of increasing signi cance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving e ficiency and driver's moods. It first identi fies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classi cation of driving moods, promoting the identifi cation of either regular or aggressive driving patterns, and the classi fication of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across diff erent vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). It is also supported by a doctoral grant, SFRH/BD/78713/2011, issued by FCT in Portugal

Prevention and Compensation of Muddy Flows: Some Economic Insights.

Recent surveys report the increasing number of muddy flows in many areas, and point out the fact that agricultural practices (among others) influence significantly the risk and severity of muddy flows. In this paper, we investigate the economic incentives that can be given to the farmer to adopt different practices. We propose an original economic instrument that entails an `ambient tax', voluntary revelations and a compensation fund. Because of the authorities' difficulties to be informed of each farmer's individual efforts, the tax cannot depend on the individual but on the collective level of efforts. However, each agent may lower his tax payment by revealing his individual efforts to the regulator so that high efforts may be rewarded compared to low ones. The tax revenue is used to supply a fund that is dedicated to the compensation of victims if a muddy flow occurs. hence it is possible to simultaneously increase the incentives for farmers to adopt more environmentally friendly practices and to improve the compensation of victims without mitigating their incentives to protect themselves against the risk of muddy flow.muddy flow, natural disasters, economic incentives, ambient tax, insurance, compensation fund.

Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C

Whole-economy scenarios for limiting global warming to 1.5C suggest that direct carbon emissions in the buildings sector should decrease to almost zero by 2050, but leave unanswered the question how this could be achieved by real-world policies. We take a modelling-based approach for simulating which policy measures could induce an almost-complete decarbonisation of residential heating, the by far largest source of direct emissions in residential buildings. Under which assumptions is it possible, and how long would it take? Policy effectiveness highly depends on behavioural decision- making by households, especially in a context of deep decarbonisation and rapid transformation. We therefore use the non-equilibrium bottom-up model FTT:Heat to simulate policies for a transition towards low-carbon heating in a context of inertia and bounded rationality, focusing on the uptake of heating technologies. Results indicate that the near-zero decarbonisation is achievable by 2050, but requires substantial policy efforts. Policy mixes are projected to be more effective and robust for driving the market of efficient low-carbon technologies, compared to the reliance on a carbon tax as the only policy instrument. In combination with subsidies for renewables, near-complete decarbonisation could be achieved with a residential carbon tax of 50-200Euro/tCO2. The policy-induced technology transition would increase average heating costs faced by households initially, but could also lead to cost reductions in most world regions in the medium term. Model projections illustrate the uncertainty that is attached to household behaviour for prematurely replacing heating systems

Traffic expression through ubiquitous and pervasive sensorization - smart cities and assessment of driving behaviour

The number of portable and wearable devices has been increasing in the population of most developed countries. Meanwhile, the capacity to monitor and register not only data about people’s habits and locations but also more complex data such as intensity and strength of movements has created an opportunity to their contribution to the general wealth and sustainability of environments. Ambient Intelligence and Intelligent Decision Making processes can benefit from the knowledge gathered by these devices to improve decisions on everyday tasks such as planning navigation routes by car, bicycle or other means of transportation and avoiding route perils. Current applications in this area demonstrate the usefulness of real time system that inform the user of conditions in the surrounding area. Nevertheless, the approach in this work aims to describe models and approaches to automatically identify current states of traffic inside cities and relate such information with knowledge obtained from historical data recovered by ubiquitous and pervasive devices. Such objective is delivered by analysing real time contributions from those devices and identifying hazardous situations and problematic sites under defined criteria that has significant influence towards user well-being, economic and environmental aspects, as defined is the sustainability definition

Towards responsive Sensitive Artificial Listeners

This paper describes work in the recently started project SEMAINE, which aims to build a set of Sensitive Artificial Listeners – conversational agents designed to sustain an interaction with a human user despite limited verbal skills, through robust recognition and generation of non-verbal behaviour in real-time, both when the agent is speaking and listening. We report on data collection and on the design of a system architecture in view of real-time responsiveness