Ultra-Low Power and Non-intrusive Wireless Monitoring for Smart Buildings

Wireless Sensor Networks (WSNs) offer a new solution for distributed monitoring, processing and communication. First of all, the stringent energy constraints to which sensing nodes are typically subjected. WSNs are often battery powered and placed where it is not possible to recharge or replace batteries. Energy can be harvested from the external environment but it is a limited resource that must be used efficiently. Energy efficiency is a key requirement for a credible WSNs design. From the power source's perspective, aggressive energy management techniques remain the most effective way to prolong the lifetime of a WSN. A new adaptive algorithm will be presented, which minimizes the consumption of wireless sensor nodes in sleep mode, when the power source has to be regulated using DC-DC converters. Another important aspect addressed is the time synchronisation in WSNs. WSNs are used for real-world applications where physical time plays an important role. An innovative low-overhead synchronisation approach will be presented, based on a Temperature Compensation Algorithm (TCA). The last aspect addressed is related to self-powered WSNs with Energy Harvesting (EH) solutions. Wireless sensor nodes with EH require some form of energy storage, which enables systems to continue operating during periods of insufficient environmental energy. However, the size of the energy storage strongly restricts the use of WSNs with EH in real-world applications. A new approach will be presented, which enables computation to be sustained during intermittent power supply. The discussed approaches will be used for real-world WSN applications. The first presented scenario is related to the experience gathered during an European Project (3ENCULT Project), regarding the design and implementation of an innovative network for monitoring heritage buildings. The second scenario is related to the experience with Telecom Italia, regarding the design of smart energy meters for monitoring the usage of household's appliances.

Design and characterization of wideband Hall current sensors in BCD technology for smart power and metering applications

Power electronic circuits are moving towards higher switching frequencies, exploiting the capabilities of novel devices to shrink the dimension of passive components. This trend demands sensors capable enough to operate at such high frequencies. This thesis aims to demonstrate through experimental characterization, the broadband capability of a fully integrated CMOS X-Hall current sensor in current mode interfaced with a transimpedance amplifier (TIA), chip CH09, realized in CMOS technology for power electronics applications such as power converters. The system exploits a common-mode control system to operate the dual supply system, 5-V for the X-Hall probe and 1.2-V for the readout. The developed prototype achieves a maximum acquisition bandwidth of 12 MHz, a power consumption of 11.46 mW, resolution of 39 mArms, a sensitivity of 8 % /T, and a FoM of 569-MHz/A2mW, significantly higher than current state-of-the-art. Further enhancements were proposed to CH09 as a new chip CH100, aiming for accuracy levels prerequisite for a real-time power electronic application. The TIA was optimized for a wider bandwidth of 26.7 MHz with nearly 30% reduction of the integrated input referred noise of 26.69 nArms at the probe-AFE interface in the frequency band of DC-30 MHz, and a 10% improvement in the dynamic range. The expected input range is 5-A. The chip incorporates a dual sensing chain for differential sensing to overcome common mode interferences. A novel offset cancellation technique is proposed that would require switching of polarity of bias currents. Thermal gain drift was improved by a factor of 8 and will be digitally calibrated utilizing a new built-in temperature sensor with a post calibration measurement accuracy greater than 1%. The estimated power consumption of the entire system is 55.6 mW. Both prototypes have been implemented through a 90-nm microelectronic process from STMicroelectronics and occupy a silicon area of 2.4 mm2.

Essays in macroeconomics: insurance, market power, and inequality

This thesis investigates a broad range of topics related to insurance, market power, and inequality, both from an empirical and a theoretical perspective. In the first chapter, I exploit the significant heterogeneity of the shocks hitting Ethiopian households and their heterogeneous response, using relatively recent data (World Bank's LSMS-ISA for households and satellite data for weather shocks). On the one hand, households seem able to insure against most idiosyncratic and mild adverse weather shocks. On the other hand, vulnerability to stronger weather shocks (especially droughts) remains elevated. In the second chapter, starting from firms' individual data, aggregate trends about industry concentration and other proxies of competition are built. This chapter is part of a larger project conducted at the OECD in the Productivity Innovation and Entrepreneurship Division of the STI Directorate The project innovates on the existing literature in its measurement of concentration, aimed at reflecting markets more accurately. On average, aggregate concentration is found to be increasing. In the third chapter, which only lays out some preliminary steps of a more extensive inquiry, I model the heterogeneous effects of aggregate technological progress on individual economic agents and show how this can affect aggregate inequality and other aggregate indicators studied in the macroeconomics literature, such as the entrepreneurship rate and the overall firm distribution. It should be noted, however, that this note is a simple exposition of a possible modelling device rather than a full explanation of these phenomena.

Gli assetti proprietari e di controllo nell'agroalimentare italiano

The recent default of important Italian agri-business companies provides a challenging issue to be investigated through an appropriate scientific approach. The events involving CIRIO, FERRUZZI or PARMALAT rise an important research question: what are the determinants of performance for Italian companies in the Italian agri – food sector? My aim is not to investigate all the factors that are relevant in explaining performance. Performance depends on a wide set of political, social, economic variables that are strongly interconnected and that are often very difficult to express by formal or mathematical tools. Rather, in my thesis I mainly focus on those aspects that are strictly related to the governance and ownership structure of agri – food companies representing a strand of research that has been quite neglected by previous scholars. The conceptual framework from which I move to justify the existence of a relationship between the ownership structure of a company, governance and performance is the model set up by Airoldi and Zattoni (2005). In particular the authors investigate the existence of complex relationships arising within the company and between the company and the environment that can bring different strategies and performances. They do not try to find the “best” ownership structure, rather they outline what variables are connected and how they could vary endogenously within the whole economic system. In spite of the fact that the Airoldi and Zattoni’s model highlights the existence of a relationship between ownership and structure that is crucial for the set up of the thesis the authors fail to apply quantitative analyses in order to verify the magnitude, sign and the causal direction of the impact. In order to fill this gap we start from the literature trying to investigate the determinants of performance. Even in this strand of research studies analysing the relationship between different forms of ownership and performance are still lacking. In this thesis, after a brief description of the Italian agri – food sector and after an introduction including a short explanation of the definitions of performance and ownership structure, I implement a model in which the performance level (interpreted here as Return on Investments and Return on Sales) is related to variables that have been previously identified by the literature as important such as the financial variables (cash and leverage indices), the firm location (North Italy, Centre Italy, South Italy), the power concentration (lower than 25%, between 25% and 50% and between 50% and 100% of ownership control) and the specific agri – food sector (agriculture, food and beverage). Moreover we add a categorical variable representing different forms of ownership structure (public limited company, limited liability company, cooperative) that is the core of our study. All those variables are fully analysed by a preliminary descriptive analysis. As in many previous contributions we apply a panel least squares analysis for 199 Italian firms in the period 1998 – 2007 with data taken from the Bureau Van Dijck Dataset. We apply two different models in which the dependant variables are respectively the Return on Investments (ROI) and the Return on Sales (ROS) indicators. Not surprisingly we find that companies located in the North Italy representing the richest area in Italy perform better than the ones located in the Centre and South of Italy. In contrast with the Modigliani - Miller theorem financial variables could be significant and the specific sector within the agri – food market could play a relevant role. As the power concentration, we find that a strong property control (higher than 50%) or a fragmented concentration (lower than 25%) perform better. This result apparently could suggest that “hybrid” forms of concentrations could create bad functioning in the decision process. As our key variables representing the ownership structure we find that public limited companies and limited liability companies perform better than cooperatives. This is easily explainable by the fact that law establishes that cooperatives are less profit – oriented. Beyond cooperatives public limited companies perform better than limited liability companies and show a more stable path over time. Results are quite consistent when we consider both ROI and ROS as dependant variables. These results should not lead us to claim that public limited company is the “best” among all possible governance structures. First, every governance solution should be considered according to specific situations. Second more robustness analyses are needed to confirm our results. At this stage we deem these findings, the model set up and our approach represent original contributions that could stimulate fruitful future studies aimed at investigating the intriguing issue concerning the effect of ownership structure on the performance levels.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.