Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

City Data Fusion: Sensor Data Fusion in the Internet of Things

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

Bringing pervasive embedded networks to the service cloud: a lightweight middleware approach

The emergence of novel pervasive networks that consist of tiny embedded nodes have reduced the gap between real and virtual worlds. This paradigm has opened the Service Cloud to a variety of wireless devices especially those with sensorial and actuating capabilities. Those pervasive networks contribute to build new context-aware applications that interpret the state of the physical world at real-time. However, traditional Service-Oriented Architectures (SOA), which are widely used in the current Internet are unsuitable for such resource-constraint devices since they are too heavy. In this research paper, an internetworking approach is proposed in order to address that important issue. The main part of our proposal is the Knowledge-Aware and Service-Oriented (KASO) Middleware that has been designed for pervasive embedded networks. KASO Middleware implements a diversity of mechanisms, services and protocols which enable developers and business processing designers to deploy, expose, discover, compose, and orchestrate real-world services (i.e. services running on sensor/actuator devices). Moreover, KASO Middleware implements endpoints to offer those services to the Cloud in a REST manner. Our internetworking approach has been validated through a real healthcare telemonitoring system deployed in a sanatorium. The validation tests show that KASO Middleware successfully brings pervasive embedded networks to the Service Cloud

ANGELAH: A Framework for Assisting Elders At Home

The ever growing percentage of elderly people within modern societies poses welfare systems under relevant stress. In fact, partial and progressive loss of motor, sensorial, and/or cognitive skills renders elders unable to live autonomously, eventually leading to their hospitalization. This results in both relevant emotional and economic costs. Ubiquitous computing technologies can offer interesting opportunities for in-house safety and autonomy. However, existing systems partially address in-house safety requirements and typically focus on only elder monitoring and emergency detection. The paper presents ANGELAH, a middleware-level solution integrating both ”elder monitoring and emergency detection” solutions and networking solutions. ANGELAH has two main features: i) it enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and ii) provides a solid framework for creating and managing rescue teams composed of individuals willing to promptly assist elders in case of emergency situations. A prototype of ANGELAH, designed for a case study for helping elders with vision impairments, is developed and interesting results are obtained from both computer simulations and a real-network testbed

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

Towards a Formal Framework for Mobile, Service-Oriented Sensor-Actuator Networks

Service-oriented sensor-actuator networks (SOSANETs) are deployed in health-critical applications like patient monitoring and have to fulfill strong safety requirements. However, a framework for the rigorous formal modeling and analysis of SOSANETs does not exist. In particular, there is currently no support for the verification of correct network behavior after node failure or loss/addition of communication links. To overcome this problem, we propose a formal framework for SOSANETs. The main idea is to base our framework on the \pi-calculus, a formally defined, compositional and well-established formalism. We choose KLAIM, an existing formal language based on the \pi-calculus as the foundation for our framework. With that, we are able to formally model SOSANETs with possible topology changes and network failures. This provides the basis for our future work on prediction, analysis and verification of the network behavior of these systems. Furthermore, we illustrate the real-life applicability of this approach by modeling and extending a use case scenario from the medical domain.Comment: In Proceedings FESCA 2013, arXiv:1302.478