Technologies for the acquisition, storage and mining of big data are increasingly affecting the Architecture, Engineering and Construction (AEC) industry, modifying the way buildings are conceived and developed. Indeed, they will be no longer designed and managed only as financial products, but also as service providers to support the needs of the occupants. This is a great challenge in the building sector, that is experiencing a period of various (r)evolution concerning products, technologies and processes. This research defines a digitally enabled framework for operating cognitive buildings, presenting a case study by which it has been possible to analyze how information collected during operations could inform end-users (i.e. administrators, owners, facility managers and occupants) about the behavior of both buildings and occupants. Focusing on building in-use stages, advantages in tracking the behavior of occupants and in satisfying the needs of users should be derived through the availability of real-time information, i.e. collected by sensors. In this way, not only the behavior of users could be taken into account, but also predicted performance could be correlated with real measurement and, consequently, the building performance gap should be estimated and filled. A connection between as-designed virtual models (resulted from a BIM - Building Information Modeling - process) and as-delivered physical assets (monitored in real-time, i.e. through BMS - Building Management Systems) could be established to explore how BIM practices and technologies could improve a data-driven asset management, by enriching building information in operation. The results should allow pointing out how data and information gathered along building life cycle could provide services to users.

As the number of installed Battery Energy Storage Systems (BESSs) increases, the concerns related to possible cyber-attacks to these systems rise accordingly. The most of BESS owners knows their systems may be vulnerable, but they often consider only denial of service attacks in their risk assessment. Unfortunately, other, subtler and more dangerous attacks exist. In this paper we show that a stealth attack to BESSs can be performed by applying a Man-in-the-Middle (MitM) approach. The aim of the attack is to stealthily manage the physical system by hiding the actual behavior of the system to its supervisory controller. In this case the attacker would be able to: (i) degrade the BESS by reducing its expected lifetime, (ii) produce economic losses for the prosumer, and (iii) affect the security and stability of the grid. The feasibility of the attack is demonstrated by providing an example of a stealth MitM attack on a real BESS coupled with a photovoltaic power plant. The proposed case study demonstrates that such attack can be performed without being discovered by end-users and shows that its effects can be severe. Finally, possible strategies to avoid or detect such kind of attack are discussed.

The wide penetration of Distributed Energy Resources (DERs) is causing a progressive decrease of the quality of energy provided by Distribution Service Operator (DSO). The management of the DERs requires improvement in control of distribution grid, which can take the advantage of ICT technologies. In literature, the integration of communication infrastructure, distributed control and distribution grid is called Smart Grid (SG). However, an optimal grid management should take into account the behavior of the customers, which are playing a more and more active role in the distribution grid. An abstraction layer is required to simplify the management of each active customer. The Energy Management System (EMS) of Smart Building provides this abstraction layer, by means of which is possible to schedule energy consumption and generation. In the paper, the Internet of Thing (IoT) approach has been applied in the deployment of an Energy Management System (EMS), designed for monitoring and supervise the distribution grid of the campus of the University of Brescia. This approach is able to provide the required flexibility, since new services can be easily implemented over the deployed framework. Preliminary results are showing the integration of a meteorological station within the system with services suitable both for humans as well as machines interactions opening the opportunity of new, independent applications.

The rise of Internet of Things (IoT) has impacted the industrial automation world. Traditional fleldbus and new fieldbus based on Real Time Ethernet (as PROFINET) have been challenged to include IoT solutions, whose real possibilities are still under evaluation. On the other hand, there are properties of industrial automation devices (e.g. robustness, “proven in use”, explosion proof) that may be useful also in typical IoT scenarios (e.g. building automation). Therefore, the paper proposes a reversed approach, where a new architecture enables the use of existing, legacy, industry-grade devices (e.g. PROFINET Sensors, actuators, and Programmable Logic controllers - PLC) to be used across the Internet. In the proposed system, the PROFINET network can be put into work by means of transparent proxies that use IoT paradigms. The paper presents and discusses a set of basic requirements and a preliminary performance evaluation of a sample application. The results show that the 99-percentile of the transfer time (from proxy to proxy) in the proposed system is less than 100ms, and it is stable even varying the PROFINET cycle time.

In the last few years, several wearables appeared in the market, for fitness and healthcare applications. Such smart devices have been proposed as a possible solution for lowering the costs of healthcare, leading to the mHealth revolution. In the typical scenario, each wearable, embedding sensors, processing units and communication modules, adopts a smartphone for data collection, data displaying, and remote communication. In this paper, authors modify this paradigm simplifying the wearables (e.g., relying only on simple analog front ends and communication interfaces) and exploiting the (relatively large) computational capability of the smartphone, not only for implementing gateway features but also for processing raw biosignals as well. Several experiments verify the feasibility of the proposed approach and demonstrate that “local” biosensor virtualization is possible, expanding possibilities of mHealth. In particular, tests have been carried out to evaluate the performance of hearth rate computation and respiratory rate virtual sensor, starting from a single-lead electrocardiogram signal.

Many different application domains are taking advantage from the adoption of the Internet of Things (IoT) paradigm. Among them, intelligent transportation systems can improve efficiency and sustainability by exploiting increased awareness about the actual mobility resource availability. For this reason, the idea of mobility as a service is gaining consensus. However, satisfying the requirements of very heterogeneous scenarios can be really challenging. In this work, we propose adding redundancy and diversity to the IoT platforms to improve overall resilience and flexibility, other than mitigating unstable behaviors. A proof-of-concept prototype is realized around a commercial IoT platform natively intended for the automotive domain. New “paths” from the vehicles to the end users, different from the original one, are added for retrieving the information: one additional LoRaWAN trunk and the other two via IBM Cloud service. A methodology for performance evaluation is suggested, computing purposely defined metrics. When applied to a sample use case, experimental results show that the redundancy and diversity strategies, compared to the (best) single-path approach, halve the overall average transfer delay (from about 1.2 s down to about 0.5 s) and the standard deviation (from about 0.5 to about 0.3 s).