Number Of Additional Sensors Research Articles

Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree.

Network science-based analysis of the observability of dynamical systems has been a focus of attention over the past five years. The maximum matching-based approach provides a simple tool to determine the minimum number of sensors and their positions. However, the resulting proportion of sensors is particularly small when compared to the size of the system, and, although structural observability is ensured, the system demands additional sensors to provide the small relative order needed for fast and robust process monitoring and control. In this paper, two clustering and simulated annealing-based methodologies are proposed to assign additional sensors to the dynamical systems. The proposed methodologies simplify the observation of the system and decrease its relative order. The usefulness of the proposed method is justified in a sensor-placement problem of a heat exchanger network. The results show that the relative order of the observability is decreased significantly by an increase in the number of additional sensors.

Sensor Synthesis for POMDPs with Reachability Objectives

Partially observable Markov decision processes (POMDPs) are widely used in probabilistic planning problems in which an agent interacts with an environment using noisy and imprecise sensors. We study a setting in which the sensors are only partially defined and the goal is to synthesize “weakest” additional sensors, such that in the resulting POMDP, there is a small-memory policy for the agent that almost-surely (with probability 1) satisfies a reachability objective. We show that the problem is NP-complete, and present a symbolic algorithm by encoding the problem into SAT instances. We illustrate trade-offs between the amount of memory of the policy and the number of additional sensors on a simple example. We have implemented our approach and consider three classical POMDP examples from the literature, and show that in all the examples the number of sensors can be significantly decreased (as compared to the existing solutions in the literature) without increasing the complexity of the policies.

PERFORMANCE OF AN OFF-BOARD TEST RIG FOR AN AUTOMOTIVE AIR CONDITIONING SYSTEM

An off-board test bench has been developed for evaluating the performance of an automotive air conditioning system. The facility consists of the mechanical hardware used in an automobile along with a large number of additional sensors and a standalone control system that mimics the operations in a car. The performance of the individual components and the system has been investigated for two major independent variables of running automobiles, namely the compressor speed and the speed of the evaporator fan. Correlations for the volumetric efficiency of the compressor and COP of the system have been developed. While the refrigerant flow rate is influenced mainly by compressor speed, the COP depends on both the operating variables. The investigation also establishes that the design of the rig, the selection and placement of the sensors and the method of measurement are suitable for its further deployment under dynamic condition and for fault diagnosis.

Naturalistic Driving Observations of Manual and Visual–Manual Interactions with Navigation Systems and Mobile Phones While Driving

This paper discusses a naturalistic driving study on the use of mobile phones and navigation systems while driving. Manual interactions with these devices while driving can cause distraction from the driving task and reduce traffic safety. In this study 21 subjects were observed for 5 weeks. Their behavior was logged by four cameras, a Global Positioning System sensor, and a number of additional sensors. Results are presented on the durations and frequencies of manual interactions with the mobile phone and navigation system. Different manual subtasks with different levels of visual interaction are discussed, as well as how these interactions relate to driving speed. Results show that participants spent on average 1% of their driving time interacting with the navigation system and 4% of their driving time interacting with the mobile phone, excluding mobile phone conversations. For the mobile phone, 48% of the interactions took longer than 15 s; for the navigation system it was 40%. The average duration of a visual–manual subtask for the navigation system and the mobile phone was not significantly different when the task was performed while driving or while the vehicle was standing still. Exploratory analysis of vehicle speed suggests that drivers do not seem to adjust their speed while performing a visual–manual task. The results are discussed in relation to traffic safety and recommendations for future research.

A novel framework for energy-efficient data gathering with random coverage in wireless sensor networks

In wireless sensor networks, different applications feature different requirements in terms of such performance metrics as sensing coverage and data reporting latency. In most applications, it is usually sufficient to provide a Desired Sensing Coverage (DSC) lower than full coverage at any instance with the guarantee that the whole area will eventually be covered within a specified delay bound. Due to the fact that these applications are also expected to run for longer periods of time and at the same time battery recharging and replacement are costly, energy consumption in wireless sensor networks should be minimized while achieving the application goals. In this article, we propose a novel framework for application-specific data gathering which exploits a trade-off between coverage and latency, thereby minimizing energy consumption and extending the network lifetime. The proposed energy-efficient, constant-time, randomized scheme, called Coverage-Adaptive raNdom SEnsor sElection (CANSEE), selects a subset of k sensors to report at each round so as to fulfill the application-specific requirement of desired sensing coverage and bounded latency, instead of always guaranteeing full coverage and minimum latency. We present a probabilistic model to estimate: (i) the connectivity of those selected k sensors and the number of additional sensors needed to guarantee connectivity; (ii) a lower bound on k in each round; and (iii) the probability of almost surely having k data reporters using the Chernoff bound. The immediate event detection capability achieved by the proposed CANSEE scheme is also analyzed to compare the performance of our framework with other data gathering schemes that allow 100% coverage. Simulation results demonstrate that our framework leads to a significant conservation of energy (and thus extended network lifetime) with a small trade-off between coverage and data reporting latency, yet providing the required data reporting capability.

Direct and blockwise identification of decomposable systems using recursive least-squares algorithm

It is demonstrated that when the system to be identified is blockwise decomposable, additional advantages can be obtained by blockwise identification with recursive least-squares (RLS) identification algorithms. The following aspects are considered: (a) reduced computational burden; (b) lessened memory storage; (c) relaxed severity of the richness requirement on the exogenous input signals. The price paid for all these is the additional number of sensors used to tap the intermediate system states.