5,623 research outputs found
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
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Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings
An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance.
The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings
Context-aware mobile applications design: implications and challeges for a new indusy
Context-aware computing is slowly becoming the new mobile paradigm in which applications can discover and use information “out and about”. Typical sources of knowledge about context are the device’s location, data about the environment at large, the mobile device’s prior activity log and even the user’s biometrics. The mobile industry agrees that this paradigm improves the appeal and value of applications by personalising and adapting them to the context in which they run. However, capturing contextual information and processing it to enhance or create a new application is a daunting task: it involves scattered systems and infrastructures and an increasingly wide array of heterogeneous data, architectures and technological tools. In this paper, we explore and analyse existing mobile context-aware applications and the proposed frameworks that enable them. The paper aims to clarify the echnological choices behind context-aware mobile applications and the challenges that still remain ahead for this area to fulfil the promises it offers
Federated Embedded Systems – a review of the literature in related fields
This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous
computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways
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Context-awareness for mobile sensing: a survey and future directions
The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions
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