Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

The energy efficiency management at urban scale by means of integrated modelling

Innovative technologies such as ICTs are recognized as being a key player against climate change and the use of sensors and actuators can efficiently control the whole energy chain in the Smart Thermal Grids at district level. On the other side, advances on 3D modelling, visualization and interaction technologies enable user profiling and represent part of the holistic approach which aims at integrating renewable energy solutions in the existing building stock. To unlock the potentiality of these technologies, the case study selected for this research focuses on interoperability between Building Information Models (BIM), GIS (Geographic Information System) models and Energy Analysis Models (EAM) for designing Renewable Energy Strategies (RES) among the demonstrator. The objectives aims at making a whole series of data concerning the energy efficiency and reduction at district level usable for various stakeholders, by creating a District Information Model (DIM). The described system also integrates BIM and district level 3D models with real-time data from sensors to analyse and correlate buildings utilization and provide real-time energy-related behaviours. An important role is played by the energy simulation through the EAM for matching measured and simulated data and to assess the energy performance of buildings starting from a BIM model or shared data. With this purpose interoperability tests are carried out between the BIM models and quasi-steady energy analysis tools in order to optimize the calculation of the energy demand according to the Italian technical specification UNI TS 11300. Information about the roofs slope and their orientation from the GIS model are used to predict the use of renewable energy – solar thermal and PV – within the selected buildings (both public and private) of the demonstrator in Turin, Italy. The expected results are a consistent reduction in both energy consume and CO2 emissions by enabling a more efficient energy distribution policies, according to the real characteristics of district buildings as well as a more efficient utilization and maintenance of the energy distribution network, based on social behaviour and users attitudes and demand. In the future the project will allow open access with personal devices and A/R visualization of energy-related information to client applications for energy and cost-analysis, tariff planning and evaluation, failure identification and maintenance, energy information sharing in order to increase the user’s awareness in the field of energy consumption

Participatory Patterns in an International Air Quality Monitoring Initiative

The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.Comment: 17 pages, 6 figures, 1 supplementary fil

Towards an ontology driven approach for systems interoperability and energy management in the smart city

Modern Information and Communication Technologies are definitely a key factor to develop the green and sustainable applications that the so-called “smart city” needs. Effective management of resources, gathering and interpreting data as well as ecological considerations are prerequisites to turn such a vision into reality. The European FP7 project DIMMER address these issues by providing a flexible Internet of Thing platform for application development and data integration, exploiting information about buildings, energy distribution grids and user behaviors. Among those applications, the possibility to real-time access and aggregate information about building environmental characteristics and energy consumption enables the optimization of energy management and control, as well as the user’s awareness about, which is the scope of the DIMMER project. The paper will describe the ontology-driven approach, as well as the actual design, exploited to model the physical world within the context of this project, adding a special emphasis on the state of art research in the field of energy profiling

Measuring Kinematic Variables in Front Crawl Swimming Using Accelerometers: A Validation Study

Objective data on swimming performance is needed to meet the demands of the swimming coach and athlete. The purpose of this study is to use a multiple inertial measurement units to calculate Lap Time, Velocity, Stroke Count, Stroke Duration, Stroke Rate and Phases of the Stroke (Entry, Pull, Push, Recovery) in front crawl swimming. Using multiple units on the body, an algorithm was developed to calculate the phases of the stroke based on the relative position of the body roll. Twelve swimmers, equipped with these devices on the body, performed fatiguing trials. The calculated factors were compared to the same data derived to video data showing strong positive results for all factors. Four swimmers required individual adaptation to the stroke phase calculation method. The developed algorithm was developed using a search window relative to the body roll (peak/trough). This customization requirement demonstrates that single based devices will not be able to determine these phases of the stroke with sufficient accuracy