Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine and report risky driver behavior.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A new kind of active protection system (APS) called SNAP (scalable networked active protection) will be a light and affordable means of protecting vehicles and infrastructure against rockets and missiles. The APS system is built from modules, each of which is itself a stand-alone APS. Since each unit is a stand-alone APS, the only single points of failure are the User Interface (UI) in the vehicle cab and the Data/Power Router (DPR). SNAP instead takes advantage of each module protecting a relatively small area to employ vastly lower cost components. In addition, each SNAP module is disposable in that when its countermunition is initiated, the entire module is consumed and subsequently replaced in the field. This approach allows the system to be very compact and lightweight.

Abstract: To reliably detect an object such as a bicycle at increased range, an Advanced Driving Support System uses a deep neural network(s) to process an ambient (grey-scale) image into an object that is then tracked by a second range detection camera. Most objects of interest, such as bicycles and automobiles, are outfitted with one or more retroreflectors that are used to cue the neural network to the object of most interest. As the retroreflectors also tend to saturate the range detection camera, a method is used to manage the saturation and estimate the correct range to the object.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine and report risky driver behavior.

Abstract: A relatively low-cost sensor can accurately detect, identify and track rapidly moving objects such as missiles, rocket propelled grenades (RPGs), mortars, explosive-driven fragments, bullets, shells, sports projectiles (baseballs, golf balls, tennis balls, arrows, etc.), and other types of objects. Systems that would incorporate such a sensor include military devices such as Active Protection System (APS), warning sensor systems, counter-fire systems; commercial devices such as an accurate baseball strike zone monitor, tennis ball line monitors, and arrow speed and flight characteristics monitors. The optical sensing system detects, identifies and tracks rapidly moving objects. The system is designed to be low-cost, rugged, highly reliable, and have a low False Alarm Rate (FAR). The system can accurately record signals from rapidly moving targets and then process this information with sufficient time to send a firing signal or take other action as appropriate.

Abstract: An integrated sensor apparatus capable of detecting exercise equipment parameters such as power output and cadence is designed so as to be easily retrofittable to existing equipment. To the extent that a particular sensor uses friction measurement, it can supplant an existing friction causing device on the equipment. Additionally, the sensor can communicate, wirelessly if desired, with a processing device. The processing device is capable of receiving and processing a plurality of sensor signals. The processing device can then output processed signals to a display, so that a plurality of people joining in a group exercise or competition can easily track their relative performance in real-time.

Abstract: A motion-coupled visual environment prevents, reduces and/or treats motion sickness by sensing inertial motion and providing a corresponding evocative image for a subject to view, Inertial sensors may include accelerometers, gyroscopes or a variety of other different sensor types. A cross-coupling algorithm may be used to cross couple different sensed inertial motions. A variety of mapping schemes may be used to map sensed inertial motion to corresponding motion within the evocative scene displayed on the display. Driver-centric, passenger-centric and simulation surround systems are possible. Applications include reducing motion sickness on passenger vehicles such as airplanes, trains and cars; on military vehicles such as ships, airplanes, helicopters and the like; and reducing “cybersickness” in the context of simulations on moving platforms.

Abstract: “Smartmat” (Smartmat Area Activity Monitor and Personnel Identification System) monitors and identifies people, animals and other objects that pass through a control volume. Among other attributes, the exemplary system implementation can count, classify and identify objects, such as pedestrians, animals, bicycles, wheelchairs, vehicles, rollerbladers and other objects, either singly or in groups. Exemplary Smartmat implementations differentiate objects based on weight, footprint and floor/wall pressure patterns such as footfall patterns of pedestrians and other patterns. The system may be applied to security monitoring, physical activity monitoring, market traffic surveys and other traffic surveys, security checkpoint/gate monitoring, traffic light activation and other device activation such as security cameras, and other monitoring applications. Smartmat may be portable or permanently installed.