Andras Nadas

Sensor network-based countersniper system

An ad-hoc wireless sensor network-based system is presented that detects and accurately locates shooters even in urban environments. The system consists of a large number of cheap sensors communicating through an ad-hoc wireless network, thus it is capable of tolerating multiple sensor failures, provides good coverage and high accuracy, and is capable of overcoming multipath effects. The performance of the proposed system is superior to that of centralized countersniper systems in such challenging environment as dense urban terrain. In this paper, in addition to the overall system architecture, the acoustic signal detection, the most important middleware services and the unique sensor fusion algorithm are also presented. The system performance is analyzed using real measurement data obtained at a US Army MOUT (Military Operations in Urban Terrain) facility.

Radio interferometric geolocation

We present a novel radio interference based sensor localization method for wireless sensor networks. The technique relies on a pair of nodes emitting radio waves simultaneously at slightly different frequencies. The carrier frequency of the composite signal is between the two frequencies, but has a very low frequency envelope. Neighboring nodes can measure the energy of the envelope signal as the signal strength. The relative phase offset of this signal measured at two receivers is a function of the distances between the four nodes involved and the carrier frequency. By making multiple measurements in an at least 8-node network, it is possible to reconstruct the relative location of the nodes in 3D. Our prototype implementation on the MICA2 platform yields an average localization error as small as 3 cm and a range of up to 160 meters. In addition to this high precision and long range, the other main advantage of the Radio Interferometric Positioning System (RIPS) is the fact that it does not require any sensors other than the radio used for wireless communication.

Countersniper system for urban warfare

An ad-hoc wireless sensor network-based system is presented that detects and accurately locates shooters even in urban environments. The localization accuracy of the system in open terrain is competitive with that of existing centralized countersniper systems. However, the presented sensor network-based solution surpasses the traditional approach because it can mitigate acoustic multipath effects prevalent in urban areas and it can also resolve multiple simultaneous shots. These unique characteristics of the system are made possible by employing novel sensor fusion techniques that utilize the spatial and temporal diversity of multiple detections. In this article, in addition to the overall system architecture, the middleware services and the unique sensor fusion algorithms are described. An analysis of the experimental data gathered during field trials at US military facilities is also presented.

Shooter localization and weapon classification with soldier-wearable networked sensors

The paper presents a wireless sensor network-based mobilecountersniper system. A sensor node consists of a helmetmountedmicrophone array, a COTS MICAz mote for internodecommunication and a custom sensorboard that implementsthe acoustic detection and Time of Arrival (ToA) estimationalgorithms on an FPGA. A 3-axis compass providesself orientation and Bluetooth is used for communicationwith the soldiers PDA running the data fusion and the userinterface. The heterogeneous sensor fusion algorithm canwork with data from a single sensor or it can fuse ToA orAngle of Arrival (AoA) observations of muzzle blasts andballistic shockwaves from multiple sensors. The system estimatesthe trajectory, the range, the caliber and the weapontype. The paper presents the system design and the resultsfrom an independent evaluation at the US Army AberdeenTest Center. The system performance is characterized by 1-degree trajectory precision and over 95% caliber estimationaccuracy for all shots, and close to 100% weapon estimationaccuracy for 4 out of 6 guns tested.

Air Quality Monitoring with SensorMap

The mobile air quality monitoring network (MAQUMON) is presented. The system consists of a number of car-mounted sensor nodes measuring different pollutants in the air. The data points are tagged with location and time utilizing an on-board GPS. Periodically, the measurements are uploaded to a server, processed and then published on the SensorMap portal. Given a sufficient number of nodes and diverse mobility patterns, a detailed picture of the air quality in a large area will be obtained at a low cost.

Wireless Acoustic Emission Sensor Network for Structural Monitoring

The paper presents a prototype wireless system for the detection of active fatigue cracks in aging railways bridges in real-time. The system is based on a small low-cost sensor node, called an AEPod, that has four acoustic emission (AE) channels and a strain channel for sensing, as well as the capability to communicate in a wireless fashion with other nodes and a base station. AEPods are placed at fracture-critical bridge locations. The strain sensor detects oncoming traffic and triggers the AEPod out of its hibernation mode. As the train stresses the fracture-critical member, acoustic emission and strain data are acquired. The data are compressed and filtered at the AEPod and transmitted off the bridge using cell-phone communication.

Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit*

Objective:To determine whether automated identification with physician notification of the systemic inflammatory response syndrome in medical intensive care unit patients expedites early administration of new antibiotics or improvement of other patient outcomes in patients with sepsis. Design:A prospective randomized, controlled, single center study. Setting:Medical intensive care unit of an academic, tertiary care medical center. Patients:Four hundred forty-two consecutive patients admitted over a 4-month period who met modified systemic inflammatory response syndrome criteria in a medical intensive care unit. Intervention:Patients were randomized to monitoring by an electronic “Listening Application” to detect modified (systemic inflammatory response syndrome) criteria vs. usual care. The listening application notified physicians in real time when modified systemic inflammatory response syndrome criteria were detected, but did not provide management recommendations. Measurements and Main Results:The median time to new antibiotics was similar between the intervention and usual care groups when comparing among all patients (6.0 hr vs. 6.1 hr, p = .95), patients with sepsis (5.3 hr vs. 5.1 hr; p = .90), patients on antibiotics at enrollment (5.2 hr vs. 7.0 hr, p = .27), or patients not on antibiotics at enrollment (5.2 hr vs. 5.1 hr, p = .85). The amount of fluid administered following detection of modified systemic inflammatory response syndrome criteria was similar between groups whether comparing all patients or only patients who were hypotensive at enrollment. Other clinical outcomes including intensive care unit length of stay, hospital length of stay, and mortality were not shown to be different between patients in the intervention and control groups. Conclusions:Realtime alerts of modified systemic inflammatory response syndrome criteria to physicians in one tertiary care medical intensive care unit were feasible and safe but did not influence measured therapeutic interventions for sepsis or significantly alter clinical outcomes.

A Model-Integrated, Guideline-Driven, Clinical Decision-Support System

Using evidence-based guidelines to standardize the care of patients with complex medical problems is a difficult challenge. In acute care settings, such as intensive care units, the inherent problems of stabilizing and improving vital patient parameters is complicated by the division of responsibilities among different healthcare team members. Computerized support for implementing such guidelines has tremendous potential. The use of model-integrated techniques for specifying and implementing guidelines as coordinated asynchronous processes is a promising new methodology for providing advanced clinical decision support. Combined with visual dashboards, which show the status of the implemented guidelines, a new approach to computer-supported care is possible. The Vanderbilt Medical Center is applying these techniques to the management of sepsis.

Multiple simultaneous acoustic source localization in urban terrain

Experiences developing a sensor network-based acoustic shooter localization system are presented. The system is able to localize the position of a shooter and the trajectory of the projectile using observed acoustic events, such as the muzzle blast and the ballistic shockwave. The network consists of a large number of cheap sensors communicating through an ad-hoc wireless network, which enables the system to resolve multiple simultaneous acoustic sources, eliminate multipath effects, tolerate multiple sensor failures while providing good coverage and high accuracy, even in such challenging environment as urban terrain. The paper describes the hardware and software platform developed for this application and summarizes the lessons learned during the development of the system.

Weapon classification and shooter localization using distributed multichannel acoustic sensors

A wireless sensor network-based wearable countersniper system prototype is presented. The sensor board is connected to a small helmet-mounted microphone array that uses time of arrival (ToA) estimates of the ballistic shockwave and the muzzle blast to compute the angle of arrival (AoA) of both acoustic events. A low-power radio is used to form an ad-hoc multihop network that shares the detections among the nodes. Utilizing all available ToA and AoA data, a novel sensor fusion algorithm then estimates the shooter position, bullet trajectory, miss distance, caliber, and weapon type. A single sensor relying only on its own detections is able determine the shooter position when both the shockwave and the muzzle blast are detected by at least three microphones each. Even with just one shockwave and one muzzle blast detection, the miss distance and range can be accurately estimated by a single sensor. The system has been tested multiple times at the US Army Aberdeen Test Center and the Nashville Police Academy. The demonstrated performance is 1-degree trajectory precision, over 95% caliber estimation accuracy, and close to 100% weapon estimation accuracy for 4 out of the 6 guns tested.