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Many agitation and mixing processes utilize various sensors for real-time monitoring and control, which can involve complex and costly equipment. For many mixing and agitation processes, such as in dough making, as mixing energy is placed, the resistance to extension increases and then after some point it decreases again. High-quality bread is obtained by stopping mixing at or close to the maximum...
Traffic control and management is a major problem in many cities, especially in growing and big cities. Traffic signals solve the problem of traffic conflict on intersection by time division multiplexing. The efficiency of traffic flow through an intersection depends on the phases, sequence and the timing of the traffic signals. Due to randomness, traffic signal timing optimization is complex and...
Detection and classification of aggressive driving can be based on the use of physiological signals or biometric information like electrocardiogram, electro dermal activity, and respiration. This research proposes a driving performance inference system based on the signature of acceleration in the two dimensions and speed. Driving style can be categorized to: below normal, normal, aggressive, and...
This paper presents a method to measure the discipline in fleet management automation. This method is based on calculating the matching degree between the actual track and the desired track. The actual track is a sequence of points that is provided by the Global Positioning System (GPS) and the desired track is also a sequence of points that is provided by the Geographic Information System (GIS)....
This paper presents a vehicular data acquisition and analysis system for fleet management automation. It exploits On-Board Diagnostic (OBD), GPS, RFID, and WiFi technologies. Although many systems currently integrate position tracking, OBD and wireless networking to allow for remote position tracking and remote diagnostic system, few systems provide the capability to automate the fleet management...
It is challenging to classify multiple dynamic targets in wireless sensor networks based on the time-varying and continuous signals. In this paper, multiple ground vehicles passing through a region are observed by audio sensor arrays and efficiently classified. Hidden Markov Model (HMM) is utilized as a framework for classification based on multiple hypothesis testing with maximum likelihood approach...
Multisensor data fusion has many military and civilian applications due to its statistical advantages. In this work, we propose a heuristic to enhance cooperative detection of moving targets within a region that is monitored by a wireless sensor network. This heuristic is based on fuzzy dynamic weighted majority voting for decision fusion. It fuses all the local decisions of the neighboring sensor...
Classification of ground vehicles based on acoustic signals can be employed effectively in battlefield surveillance, traffic control, and many other applications. The classification performance depends on the selection of signal features that determine the separation of different signal classes. In this paper, we investigate two feature extraction methods for acoustic signals from moving ground vehicles...
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