Low-cost and distributed health monitoring system for critical buildings

In this paper we present a low-cost distributed embedded system for Structural Health Monitoring (SHM) that uses very cost-effective MEMS accelerometers, instead of more expensive piezoelectric analog transducers. The proposed platform provides online filtering and fusion of the collected data directly on-board. Data are transmitted after processing using a WiFi transceiver. Low-cost and synchronized devices permit to have more fine-grained measurements and a comprehensive assessment of the whole building, by evaluating their response to vibrations. The challenge addressed in this paper is to execute a quite computationally-demanding digital filtering on a low-cost microcontroller STM32, and to reduce the signal-to-noise ratio typical of MEMS devices with a spatial redundancy of the sensors. Our work poses the basis for low-cost methods for elaborating complex modal analysis of buildings and structures

Energy-aware task allocation for energy harvesting sensor networks

10.1186/s13638-015-0490-3Eurasip Journal on Wireless Communications and Networking201611-1

Building a green connected future: smart (Internet of) Things for smart networks

The vision of Internet of Things (IoT) promises to reshape society by creating a future where we will be surrounded by a smart environment that is constantly aware of the users and has the ability to adapt to any changes. In the IoT, a huge variety of smart devices is interconnected to form a network of distributed agents that continuously share and process information. This communication paradigm has been recognized as one of the key enablers of the rapidly emerging applications that make up the fabric of the IoT. These networks, often called wireless sensor networks (WSNs), are characterized by the low cost of their components, their pervasive connectivity, and their self-organization features, which allow them to cooperate with other IoT elements to create large-scale heterogeneous information systems. However, a number of considerable challenges is arising when considering the design of large-scale WSNs. In particular, these networks are made up by embedded devices that suffer from severe power constraints and limited resources. The advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. Green wireless networks are considered a fundamental vehicle for enabling all those critical IoT applications where devices, for different reasons, do not carry batteries, and that therefore only harvest energy and store it for future use. These networks are considered to have the potential of infinite lifetime since they do not depend on batteries, or on any other limited power sources. Wake-up radios, coupled with energy provisioning techniques, further assist on overcoming the physical constraints of traditional WSNs. In addition, they are particularly important in green WSNs scenarios in which it is difficult to achieve energy neutrality due to limited harvesting rates. In this PhD thesis we set to investigate how different data forwarding mechanisms can make the most of these green wireless networks-enabling technologies, namely, energy harvesting and wake-up radios. Specifically, we present a number of cross-layer routing approaches with different forwarding design choices and study their consequences on network performance. Among the most promising protocol design techniques, the past decade has shown the increasingly intensive adoption of techniques based on various forms of machine learning to increase and optimize the performance of WSNs. However, learning techniques can suffer from high computational costs as nodes drain a considerable percentage of their energy budget to run sophisticated software procedures, predict accurate information and determine optimal decision. This thesis addresses also the problem of local computational requirements of learning-based data forwarding strategies by investigating their impact on the performance of the network. Results indicate that local computation can be a major source of energy consumption; it’s impact on network performance should not be neglected

Energy-harvesting WSNs for structural health monitoring of underground train tunnels

Structural health monitoring is a vital tool to help engineers improving the safety of critical structures, avoiding the risks of catastrophic failures. Wireless sensor networks (WSNs) are a very promising technology for structural health monitoring, as they can provide a quality of monitoring similar to conventional (wired) SHM systems with lower cost. In addiction, WSNs are both non-intrusive and non-disruptive and can be employed from the very early stages of construction.The main goal of this work is to investigate the feasibility of a WSN with energy-harvesting capabilities for structural health monitoring, specifically targeting underground tunnels

Wireless Sensor Network Node with Energy Harvesting for Monitoring of Environmental Parameters

U disertaciji je opisan namenski projektovan bežični senzorski čvor namenjen za praćenje parametara životne sredine. Razvijeno rešenje se odlikuje malom cenom i dimenzijama, širokom primenom i minimalnim utocajem na životnu sredinu u poređenju sa primerima iz literature. Koristi se prikupljanje energije sunca iz okoline i superkondenzator za napajanje, što utiče na povećanje životnog veka i smanjivanje troškova održavanja. Izvršena testiranja su potvrdila funkcionalnost predloženog rešenja i mogućnost praćenja različitih parametara korišćenjem komercijalnih i namenski projektovanih senzora. Unapređeno, modularno, rešenje rešava uočena ograničenja i povećava broj parametara životne sredine koji se mogu pratiti.The dissertation describes a specially designed WSN node for application in environmental monitoring. The developed solution is characterized by low price and dimensions, wide application and minimal environmental impact compared to example in literature. Solar energy harvesting and supercapacitor are used as power supply, which increase node lifetime and reduce maintenance costs. The performed tests confirmed the functionality of the proposed solution and the ability to monitor various environmental parameters using commercial and specially designed sensors. The new enhanced solution, with modular design, solves the observed limitations and increases the number of environment parameters that can be monitored