Low-Complexity One-Dimensional Edge Detection in Wireless Sensor Networks

In various wireless sensor network applications, it is of interest to monitor the perimeter of an area of interest. For example, one may need to check if there is a leakage of a dangerous substance. In this paper, we model this as a problem of one-dimensional edge detection, that is, detection of a spatially nonconstant one-dimensional phenomenon, observed by sensors which communicate to an access point (AP) through (possibly noisy) communication links. Two possible quantization strategies are considered at the sensors: (i) binary quantization and (ii) absence of quantization. We first derive the minimum mean square error (MMSE) detection algorithm at the AP. Then, we propose a simplified (suboptimum) detection algorithm, with reduced computational complexity. Noisy communication links are modeled either as (i) binary symmetric channels (BSCs) or (ii) channels with additive white Gaussian noise (AWGN)

On the shock thickness for a binary gas mixture

We discuss the structure of the shock wave solution for a system of Navier–Stokes equations, obtained as hydrodynamic limit of a BGK description of the dynamics of monoatomic gases at kinetic level. We investigate first the thickness of the transition region of the shock profile for a monoatomic gas, for varying Mach number and different physical options for the viscosity coefficient. The analysis is then extended to a binary gas mixture. Some numerical results for noble gases are presented and discussed

Optimal control of leachate recirculation for anaerobic processes in landfills

A mathematical model for the degradation of the organic fraction of solid waste in landfills, by means of an anaerobic bacterial population, is proposed. Additional phenomena, like hydrolysis of insoluble substrate and biomass decay, are taken into account. The evolution of the system is monitored by controlling the effects of leachate recirculation on the hydrolytic process. We investigate the optimal strategies to minimize substrate concentration and recirculation operation costs. Analytical and numerical results are presented and discussed for linear and quadratic cost functionals

Wireless sensor networks: performance analysis in indoor scenarios

We evaluate the performance of realistic wireless sensor networks in indoor scenarios. Most of the considered networks are formed by nodes using the Zigbee communication protocol. For comparison, we also analyze networks based on the proprietary standard Z-Wave. Two main groups of network scenarios are proposed: (i) scenarios with direct transmissions between the remote nodes and the network coordinator, and (ii) scenarios with routers, which relay the packets between the remote nodes and the coordinator. The sensor networks of interest are evaluated considering different performance metrics. In particular, we show how the received signal strength indication (RSSI) behaves in the considered scenarios. Then, the network behavior is characterized in terms of end-to-end delay and throughput. In order to confirm the experiments, analytical and simulation results are also derived

Decentralized detection in IEEE 802.15.4 wireless sensor networks

We present a mathematical model to study decentralized detection in clustered wireless sensor networks (WSNs). Sensors and fusion centers (FCs) are distributed with the aim of detecting an event of interest. Sensors are organized in clusters, with FCs acting as cluster heads, and are supposed to observe the same common binary phenomenon. A query-based application is accounted for; FCs periodically send queries and wait for replies coming from sensors. After reception of data, FCs perform data fusion with a majority-like fusion rule and send their decisions to an access point (AP), where a final data fusion is carried out and an estimate of the phenomenon is obtained. We assume that sensors are IEEE 802.15.4-compliant devices and use the medium access control (MAC) protocol defined by the standard, based on carrier-sense multiple access with collision avoidance. Decentralized detection and MAC issues are jointly investigated through analytical modelling. The proposed framework allows the derivation of the probability of decision error at the AP, when accounting for packets' losses due to possible collisions. Our results show that MAC losses strongly affect system performance. The impact of different clustering configurations and of noisy communications is also investigated

Shock wave structure of multi-temperature Euler equations from kinetic theory for a binary mixture

Abstract A multi-temperature hydrodynamic limit of kinetic equations is employed for the analysis of the steady shock problem in a binary mixture. Numerical results for varying parameters indicate possible occurrence of either smooth profiles or of weak solutions with one or two discontinuities

On driver behavior recognition for increased safety:A roadmap

Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced

Feedback Power Control Strategies in Wireless Sensor Networks with Joint Channel Decoding

In this paper, we derive feedback power control strategies for block-faded multiple access schemes with correlated sources and joint channel decoding (JCD). In particular, upon the derivation of the feasible signal-to-noise ratio (SNR) region for the considered multiple access schemes, i.e., the multidimensional SNR region where error-free communications are, in principle, possible, two feedback power control strategies are proposed: (i) a classical feedback power control strategy, which aims at equalizing all link SNRs at the access point (AP), and (ii) an innovative optimized feedback power control strategy, which tries to make the network operational point fall in the feasible SNR region at the lowest overall transmit energy consumption. These strategies will be referred to as “balanced SNR” and “unbalanced SNR,” respectively. While they require, in principle, an unlimited power control range at the sources, we also propose practical versions with a limited power control range. We preliminary consider a scenario with orthogonal links and ideal feedback. Then, we analyze the robustness of the proposed power control strategies to possible non-idealities, in terms of residual multiple access interference and noisy feedback channels. Finally, we successfully apply the proposed feedback power control strategies to a limiting case of the class of considered multiple access schemes, namely a central estimating officer (CEO) scenario, where the sensors observe noisy versions of a common binary information sequence and the AP's goal is to estimate this sequence by properly fusing the soft-output information output by the JCD algorithm