https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

Wireless sensor networks for healthcare: A survey

Advances in wireless communication technologies, such as wearable and implantable biosensors, along with recent developments in the embedded computing area are enabling the design, development, and implementation of body area networks. This class of networks is paving the way for the deployment of innovative healthcare monitoring applications. In the past few years, much of the research in the area of body area networks has focused on issues related to wireless sensor designs, sensor miniaturization, low-power sensor circuitry, signal processing, and communications protocols. In this paper, we present an overview of body area networks, and a discussion of BAN communications types and their related issues. We provide a detailed investigation of sensor devices, physical layer, data link layer, and radio technology aspects of BAN research. We also present a taxonomy of BAN projects that have been introduced/proposed to date. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make BANs truly ubiquitous for a wide range of applications.

Body Area Networks: A Survey

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper.

Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring

Traffic state estimation on highway: A comprehensive survey

Sophisticated electronics are within reach of average users. Cooperation between wireless sensor networks and existing consumer electronic infrastructures can assist in the areas of health care and patient monitoring. This will improve the quality of life of patients, provide early detection for certain ailments, and improve doctor-patient efficiency. The goal of our work is to focus on health-related applications of wireless sensor networks. In this paper we detail our experiences building several prototypes and discuss the driving force behind home health monitoring and how current (and future) technologies will enable automated home health monitoring.

/pdf/wireless-sensor-networks-for-home-health-care-3mqxfqi9bu.pdf

Wireless Sensor Networks for Home Health Care

This paper will present a method for automated, empirical calibration of freeway traffic flow characteristics. The method uses 5-min flow and density values for a section of freeway and rapidly and reliably estimates key parameters such as free flow speed, capacity, critical density, congestion wave speed and jam density, which are key inputs to many macroscopic traffic simulation models. The method consists of data filtering, capacity identification, and approximate quantile regression steps. The method was used to calibrate a cell transmission model of Interstate-880 in San Francisco Bay Area, California, a 40-mile long urban freeway with lots of recurrent and non-recurrent congestion and with dozens of loop detector stations. The calibrated model reproduced the observed traffic congestion behavior within 9% error for performance measures VMT (vehicle miles traveled), VHT (vehicle hours traveled) and total flow. Also, the empirical results suggest that capacity, defined as the maximum observed 5-minute flow rate over several days, differs from breakdown flow, defined as the flow that is observed just before the freeway section becomes congested.

Automatic Calibration of the Fundamental Diagram and Empirical Observations on Capacity

This paper illustrates the calibration and imputation procedure implemented to specify the inputs to the Link-Node Cell Transmission model used for simulating traffic flow in freeways. Traffic flow and occupancy data from loop detectors is used for calibrating these models and specifying the inputs to the simulation. In addition, flow data from ramps are often found to be missing or incorrect. A model based iterative learning technique is used to impute these ramp flows by minimizing the error between simulated and measured densities. The simulation results using the calibrated parameters and imputed flows indicate good conformation with loop detector measurements.

Freeway traffic flow simulation using the Link Node Cell transmission model

TOPL is a suite of software tools for specifying freeway operational improvement strategies, such as ramp metering, demand and incident management, and for quickly estimating the benefits of such improvements. TOPL is based on the macroscopic cell transmission model. The paper summarizes the theory of the cell transmission model and describes the procedure to carry out a TOPL application. The procedure is illustrated for the 26-mile long I-210W freeway in California, whose model is calibrated using loop detector measurements of volume and speed. The measurements show that congestion originates in a bottleneck and moves upstream, as predicted by the theory. The simulations show that appropriate ramp metering can dramatically reduce total congestion delay and mainline travel time.Copyright © 2008 by ASME

/pdf/topl-tools-for-operational-planning-of-transportation-58v7qgk974.pdf

TOPL: Tools for Operational Planning of Transportation Networks

Freeway traffic simulations must account for the probabilistic nature of model parameters to capture observed variations in traffic behavior. Fundamental diagrams specify freeway section parameters describing the flow-density relationship in macroscopic simulation models. A triangular fundamental diagram—specified with the free-flow speed, congestion wave speed, and capacity—is commonly adopted in first-order cell transmission models. Capacity (defined as the maximum flow observed in a given freeway section over a particular day) exhibits significant day-to-day variation, and capacity variations across different sections of the freeway are significantly correlated. Free-flow speeds do not exhibit significant variation, but congestion wave speeds exhibit variation uncorrelated with section capacities or parameters from other sections. A probabilistic graphical approach is presented to model the probabilistic distribution of fundamental diagram parameters of an entire freeway section chosen for simulation. ...

Gunes Dervisoglu

Papers

Wireless Sensor Networks for Home Health Care

Automatic Calibration of the Fundamental Diagram and Empirical Observations on Capacity

Freeway traffic flow simulation using the Link Node Cell transmission model

TOPL: Tools for Operational Planning of Transportation Networks

Probabilistic Graphical Models of Fundamental Diagram Parameters for Simulations of Freeway Traffic