Marco Arnesano

A semantic service-oriented platform for energy efficient buildings

The construction industry is under pressure to increase the sustainability of its practices to meet UK commitments for reducing energy consumption and alleviating climate change. The research uses a mixed-method approach drawn from recent studies to explore the readiness, maturity and level of engagement of construction stakeholders in adopting the UK government sustainability agenda. Limited positive energy practices and sustainability regulatory awareness, combined with information provision deficiencies, form some of the key barriers to sustainable construction faced by industry. A service-oriented platform that provides integrated access to sustainability resources in the form of interactive, dynamic and user-oriented services that fully exploit latest advances in computing technologies is proposed to address these barriers. In this paper, we specifically elaborate on how a service-oriented system can be efficiently used for performing (near) real-time energy optimisation in buildings, greatly contributing to engaging construction stakeholders with sustainability practices. The solution disseminates energy efficient practices and provides support for building managers in implementing energy efficient optimisation plans. The solution is tested and validated through a number of energy efficiency scenarios developed as part of the EU FP7 SportE2 project.

A Low-Cost Sensor for Real-Time Monitoring of Indoor Thermal Comfort for Ambient Assisted Living

The present paper illustrates an innovative low cost solution for the monitoring of indoor thermal comfort by means of Predictive Mean Vote (PMV) index for multiple positions. This is particularly interesting in an Ambient Assisted Living environment as replacement of typical thermostat used for the climate control. In fact, the system proposed considers also personal parameters, as metabolic rate (M) and clothing level (\(I_{cl}\)), instead of the merely environmental parameters. If this is important for normal living conditions, it becomes crucial in case of elderly people and long-term care patients where a reduction of M or \(I_{cl}\) causes a high sensitivity to thermal conditions (especially for cold sensation), or where the disability does not allow the subject re-action (e.g. shading opening/closing when solar radiation occurs). The device proposed uses a set of low-cost non-contact sensors to determine, based on algorithms provided by ISO 7726 and 7730, Mean Radiant Temperature (MRT) and PMV, which are provided as output of the device through wireless or wired connection. The capability of predicting thermal comfort conditions for multiple positions of the occupant in the room has been tested and validated in a real case study: it resulted in a discrepancy of \(\pm 0.5\,^{\circ }\mathrm{C}\) in the MRT measurement and \(\pm \)0.1 for the PMV with respect to a reference measurement system (microclimate station). The sensitivity to the metabolic rate and clothing level for AAL applications is also discussed together with a procedure for an estimation of these parameters. The accuracy achieved allows a better measurement of the real thermal sensation for a more comfortable environment with lower energy consumption.

Integration of Real-Time Metabolic Rate Measurement in a Low-Cost Tool for the Thermal Comfort Monitoring in AAL Environments

The work presented illustrates a methodology to integrate the continuous estimation of metabolic rate in a monitoring tool for the indoor thermal comfort in AAL environments. The monitoring tool adopts an infrared (IR) sensor to retrieve indoor temperatures and evaluate the mean radiant temperature for multiple positions in the space. Other sensors embedded in the central unit allow the estimation of the PMV (Predicted Mean Vote) index. Beyond the ambient quantities, an accurate estimation of the personal parameters (clothing insulation and metabolic rate) allows a reliable assessment of the indoor thermal conditions. According to standards, heart rate measurement can provide an accurate estimation of metabolic rate, but the need of measuring it continuously made this method not applicable in real scenarios. However, in Ambient Assisting Living applications it is easy to monitor vital signs from the existing equipment, e.g. wearable sensors. Therefore, this paper presents the results of the integration of low-cost heart rate sensors in a tool for the monitoring of thermal comfort. The solution turned out to have an uncertainty for the metabolic rate of ±7 % of the reading in a range from 0.7 to 3.4 m, considering that the sensor used has a discrepancy of ±1.3 bpm with respect to a reference measurement system. An accuracy of ±0.05 in the PMV computation was found as result of the uncertainty in the estimation of M.