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Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System

The driving force behind the smart city initiative is to offer better, more specialized services which can improve the quality of life of the citizens while promoting sustainability. To achieve both of these apparently competing goals, services must be increasingly autonomous and continuously adaptive to changes in their environment and the information coming from other services. In this paper we focus on smart lighting, a relevant application domain for which we propose an intelligent street light control system based on adaptive behavior rules. We evaluate our approach by using a simulator which combines wireless sensor networks and belief-desire-intention (BDI) agents to enable a precise simulation of both the city infrastructure and the adaptive behavior that it implements. The results reveal energy savings of close to 35% when the lighting system implements an adaptive behavior as opposed to a rigid, predefined behavior.

Energy-neutral networked wireless sensors

Solar cells combined with power management algorithms enable the dynamic scheduling of Wireless Sensor Networks applications in a reference period, where the objective of the scheduling is to maximize the application quality level while conserving an energy level sufficient to constantly maintain the sensor operation. With the purpose of fulfillment of its activities the sensor may have alternative different applications with different costs and quality levels, which are intended to express how much the application meets the user requirements. In this paper we propose an algorithm that aims to find a (sub)optimal scheduling that maximizes the overall quality of service for two networked, solar cells powered sensors, and keeps the system energy neutral, thus ensuring that the system works uninterruptedly.

Optimization of Quality of Service in Wireless Sensor Networks Powered by Solar Cells

Sensors equipped with solar cells and rechargeable batteries are useful in many outdoor, long-lasting applications. In these sensors the cycles of energy harvesting and battery recharge need to be managed appropriately in order to avoid sensor unavailability due to energy shortages. We suggest that adapting the sensor duty cycle (and specifically its environment sampling frequency) to the expected energy production and residual battery charge is very useful to avoid sensors unavailability. To this purpose we introduce a novel concept of QoS, which is measured in terms of sampling frequency, and we provide a mean to maximize the QoS, i.e. the extent of the period in which the sensor operates at the users desired sampling frequency.

Cross Layer Adaptation of Check Intervals in Low Power Listening MAC Protocols for Lifetime Improvement in Wireless Sensor Networks

Preamble sampling-based MAC protocols designed for Wireless Sensor Networks (WSN) are aimed at prolonging the lifetime of the nodes by scheduling their times of activity. This scheduling exploits node synchronization to find the right trade-off between energy consumption and delay. In this paper we consider the problem of node synchronization in preamble sampling protocols. We propose Cross Layer Adaptation of Check intervals (CLAC), a novel protocol intended to reduce the energy consumption of the nodes without significantly increasing the delay. Our protocol modifies the scheduling of the nodes based on estimating the delay experienced by a packet that travels along a multi-hop path. CLAC uses routing and MAC layer information to compute a delay that matches the packet arrival time. We have implemented CLAC on top of well-known routing and MAC protocols for WSN, and we have evaluated our implementation using the Avrora simulator. The simulation results confirm that CLAC improves the network lifetime at no additional packet loss and without affecting the end-to-end delay.

Cross-layer optimization of Low Power Listening MAC protocols for Wireless Sensor Networks

MAC protocols for Wireless Sensor Networks based on channel checking to detect incoming packets (such as Low Power Listening, LPL) require some form of synchronization among sensors, in order to schedule the times in which the sender and the receiver should turn on their radios, and to ensure correct packet delivery. However, while travelling along multihop paths, packets may accumulate delays that force the sensors either to incur packet losses and retransmissions or to readjust the planned scheduling. In both cases this fact impacts on the energy budget of the sensors. In this paper we propose a cross-layer optimization for MAC protocols that use LPL. This optimization takes into account high-level information of the application in order to compute adaptive delays in every sensor along a multihop path, with the goal of adjusting precisely the activity time window of the sensor along the path. We validate our delay-based model by evaluating different scenarios, and we compare it against the LPL model. The simulation results confirm the validity of our approach and demonstrate that a delay-based model can improve the synchronization achieved through the LPL strategy.

Deconstructing the Wireless Sensor Networks Architecture

Nowadays there is a trend in distributed systems research of applying software engineering and open standards in the development of large, robust and easily configurable systems, where the basic unit of replacement is the software component. Literature in Wireless Sensor Networks (WSN), a recently emerging technology, shows on the contrary, an abolition of these techniques as a response to the strong restrictions imposed by the hardware. Therefore, the current software created for WSN has features of the long time ago software: monolithic and platform dependent. This work studies the current state of the art in WSN and Model Driven Architecture (MDA), a standard used to drive the development of large distributed systems. The most important contribution of this paper is fusing both into an initial version of a feasible component-based middleware addressing the major challenges in WSN.

Early Detection of Hypoglycemia Events Based on Biometric Sensors Prototyped on FPGAs

Diabetes is a chronic disease that requires continuous medical care and patient self-monitoring processes. The control of the glucose level in blood is a task that the patient needs to perform to prevent hypoglycemia episodes. Early detection of hypoglycemia is a very important element for preventing multi-organ failure. The incorporation of other biomedical parameters monitoring, combined with glucose levels can help to early detect and prevent those episodes. At this respect, several e-health platforms have been developed for monitoring and processing vital signals related to diabetes events. In this paper we evaluate a couple of these platforms and we introduce an algorithm to analyze the data of glucose, in order to anticipate the moment of an hypoglycemia episode. The proposed algorithm contemplates the information of several biomedical sensors, and it is based on the analysis of the gradient of the glucose curve, producing an estimation of the expected time to achieve a given threshold. Besides, the proposed algorithm allows to analyze the correlations of the monitored multi-signals information with diabetes related events. The algorithm was developed to be implemented on an FPGA-based SoC and was evaluated by simulation. The results obtained are very promising and can be scalable to further signals processing.

An adaptive emergency protocol for people evacuation in high-rise buildings

The occurrence of emergency situations in high-rise buildings, daily hosting hundreds of people, may force the massive evacuation of their occupants with the ultimate goal of preventing the loss of lives. In this paper, we propose an adaptive algorithm for dynamically computing safe evacuation routes, while the load of people is balanced between the accesses of each floor of the building, thus avoiding the accumulation of people in hotspots. The combination of this algorithm with sensors to detect the events of interest and a navigation system to guide the evacuees turns this solution into a specially suited approach for evacuation in high-rise buildings. Simulation results demonstrate that the yield evacuation routes drive all people outdoor with a similar average path length for the different risk scenarios addressed.

Energy management of networked, solar cells powered, wireless sensors

Solar cells combined with power management algorithms enable the dynamic scheduling of Wireless Sensor Networks applications in a reference period, where the objective of the scheduling is to maximize the application quality level while conserving an energy level sufficient to constantly maintain the sensor operation. In this paper we consider networked, solar cells powered wireless sensors and we propose an algorithm aims to find a global, (sub)optimal scheduling that maximizes the overall quality of service in the sensors and keeps the system energy neutral, thus ensuring that the system works uninterruptedly.

An open framework for translating portable applications into operating system‐specific wireless sensor networks applications

Wireless sensor networks (WSNs) are distributed systems integrated by tiny devices, called sensor nodes, with capabilities to monitor the environment and forward their measurements to a special node, the sink, where the results can be collected and further processed. The trend in WSN is moving towards heterogeneous networks that will contain different sensor nodes running different instances of custom operating systems. Given the growing demand of new hardware platforms and operating systems specifically designed for sensor nodes, the applications programming for sensor nodes is becoming a challenging process that needs to be alleviated. Currently, application programming for sensor nodes is a complex, ad hoc, and error‐prone process where the portability among different platforms has been sacrificed. In this paper, we propose an open framework aimed to achieve application portability in heterogeneous sensor networks. Our approach provides the programming abstractions needed to support the application development process for sensor nodes. We have implemented an open framework that provides a set of tools on top of the most popular WSN operating systems to translate portable applications to the native operating system in an automatic, simple, and transparent way for developers. We have also evaluated the applications thus generated in terms of productivity and overhead, by comparing their footprint to those originally developed in each specific operating system. The results show that the overhead is minimal—4% in the worst case—and in some cases, it was even possible to reduce the footprint by using code optimizations. Copyright