A sensor coil is developed for detecting personal transporters based on unique vehicle signatures. Mixed use of a wide range of personal transportation vehicles like kick scooters, skateboards and hover boards on the urban cycle lanes have led to an increased traffic on these lanes. For the planning and optimal use of such lanes, accurate information regarding the traffic on such lanes, i.e. the number and types of vehicles are needed. Most of the conventional vehicle detection schemes fail to sense these vehicles accurately due to their small size. As the vehicle size is less compared to the rider, even the computer vision based techniques confuse them as pedestrians. Inductive loop sensors have several advantages and are widely used for traffic detection of large vehicles. They provide a signature for each type of vehicle, due to the change in inductance of the sensor coil owing to the metallic bottom structure of the vehicle. The present work proposes four sensor coil designs for cycle lanes, and evaluates their performance in sensing and classifying the personal transporters. A simple coupled resonating circuit that gives high sensitivity and noise rejection capability is used to measure from the sensor coil. The sensor designs are tested with three types of vehicles, typically found on cycle lanes -electric kick scooter, bicycle and a skateboard. The vehicles are driven through various possible paths along the sensor coil and the corresponding signatures are recorded. From the observed signatures for each vehicle type, a set of attributes are identified, which could be used as inputs for any classification algorithm. The proposed designs are also evaluated based on a set of criteria, from which, one of the design is selected as the best. This study shows that, if suitably designed, inductive loop sensors can give unique signatures for personal transportation vehicles, enabling reliable detection and classification.

This paper presents an efficient method to sense the position of wirelessly charged Electric Personal Transporters (EPTs) on a charging pad array to enable the right primary coil(s) to excite, ensuring high power transfer efficiency. The proposed method makes use of the impedance of the primary coil(s) at the parallel resonance frequency to sense the position of the EPT. Sensing mechanisms reported for commercially available electric vehicles like cars are not suitable in the case of EPTs, due to the huge differences in the size and shape of the vehicle structure. A study on the impedance pattern change of a circular coil charging pad array caused by wirelessly charged EPTs is conducted. Compensated coils arranged in an array or matrix format is used to form the charging pad. EPT with a tuned receiver coil modulates the input impedance measured from primary side. Impedance measurements made at the parallel resonant frequency ensures high sensitivity with respect to change in the coupling factor. While the receiver coil causes increase in primary side impedance, the metal parts, especially battery causes the impedance to fall. Single and dual coil impedance measurements of the charging array give a reliable pattern, which on analysis is used to develop an algorithm for EPT detection and positioning on the charging pad array, enabling the system to excite the coil(s) that have maximum coupling with the vehicle pad. The study conducted, the results and the algorithm presented are useful while designing and operating charging pad array for wirelessly charged EPTs even in a relatively flexible parking environment.

Reliable automatic terrain recognition is key for numerous applications including robotics, navigation of the visually impaired, and amputees. It is a complex sensing problem and multiple modalities will be needed to improve the accuracy of recognition and reliability. Timely feedback on the type of ground surface can help in safely guiding through their path and support to prevent from slipping and falling. In this paper, a novel method to measure the ground impedance between the shoes of a person or a robot is presented. The feasibility of the scheme in supporting terrain recognition is experimentally studied and presented. Measurement of ground impedance between the shoes needs a special solution as the ground impedance comes in parallel with the relatively low-value body impedance of the person. A novel technique is proposed to bring the body impedance in series with the ground impedance as far as the measurement system is concerned. The sole of the shoe is modified by integrating flexible electrodes and conductive stitches, without affecting the comfort. A suitable electronic interface is developed to obtain the impedance value of the ground across the feet, from these modified shoes. A prototype has been developed and tested in the laboratory and in the field. Experimental results show that different terrains such as concrete, gravel, wet and dry soil, grass, marble, etc. can be distinguished based on the impedance values. The proposed method and system will be very useful in providing additional new and valuable information to the existing terrain detection systems, e.g., vision-based. A fusion of these two will improve the reliability of the automatic terrain recognition as they both provide different and independent information about the terrain.

One of the challenges faced in the design of inductive power transfer (IPT) highway is the detection of electric vehicle (EV), to enable charging, as it travels along the highway. When a primary coil buried under the highway has sufficient coupling with the secondary coil mounted on the vehicle, it is energized to initiate IPT. In this paper, a tunneling magnetoresistance (TMR) sensor based EV detection method on an IPT highway is proposed. In the proposed scheme, a detection coil is wound around the outer boundary of the secondary coil and it is excited at 400 kHz. The TMR sensors are arranged close to the primary coil such that it senses the magnetic field generated by the detection coil. The TMR sensors are placed over the leading and trailing edges (in the direction of EV travel) of the primary coil. From the leading edge TMR sensor outputs, the energization point of that primary coil to begin IPT is decided. Similarly, from the trailing edge TMR sensor outputs, the de-energization point to stop IPT from that primary coil is decided. Also, the effective area of overlap between the coils due to lateral misalignment is estimated. This enables the driver in correcting the lateral misalignment so that efficient charging is possible from the subsequent primary pads. A laboratory scale prototype was built and was tested. The results obtained prove the usefulness of the scheme.

This paper presents a non-contact inductive and capacitive coupled method of measurement of conductivity of liquids. The current through a pre-set column of liquid is established through induction. The voltage drop across the preset column of liquid is measured through capacitive coupled electrodes. The absence of contacting electrodes ensures that the method is free from effects due to contamination / corrosion of electrodes. The method proposed ensures that the measurement of the voltage drop across the column is independent of the values of the coupling capacitances of the capacitive coupled electrode. Hence, any deviation in the fabrication of the probe has negligible influence on the measured conductivity. Results obtained from a prototype unit built and tested show that the maximum relative error in the conductivity measurement is and the measured conductivity values are independent of the values of the coupling capacitors.

This paper proposes a novel probe for reliable detection of crack/defect in a conductive target. This probe is realized by combining the eddy current and capacitive sensing techniques. Lift-off is a main concern for the eddy current based defect detection systems as the output of the sensor is very sensitive to the air gap between the target and the probe. The effect is significant when the probe is kept close to the target. In the proposed probe, like in some of the conventional ones, a planar coil is used as the eddy current sensing element. The same planar coil is used as a capacitive sensing element to sense the value of the capacitance between the coil and the target. This value is a function of the air gap between the probe and the target. The measured value is fed back to a magnetic actuator on which the entire probe is fitted. The magnetic actuator uses the capacitance value information and automatically adjusts the gap between the probe and the target to a preset value. Thus, the liftoff is corrected automatically. The functionality of the new probe has been analyzed and optimized using finite element analysis before building a prototype probe. Tests conducted on the probe developed confirms the effectiveness of the probe.

This paper presents an effective multiple-inductive-loop pattern suitable for heterogeneous and less lane-disciplined traffic and its performance evaluation. Vehicle detection system based on conventional inductive loops works well only for lane-based and homogeneous traffic. A multiple-loop system for sensing vehicles in a heterogeneous and less lane-disciplined condition has been reported recently. The scheme proposed in this paper employs a new configuration, where all the loops are connected in series, which considerably reduces the system complexity and improves reliability. Each loop has a unique resonance frequency and the excitation source given to the loops is programmed to have frequency components covering all the loop resonance frequencies. When a vehicle goes over a loop, the corresponding inductance and resonance frequency will change. The shift in frequency or its effect in any/every loop can be simultaneously monitored, and the vehicles can be detected and identified as a bicycle, a motorcycle, a car, a bus, etc., based on the signature. Another advantage of this scheme is that the loops are in parallel resonance; hence, the power drawn from the source will be minimal. A prototype multiple-loop system has been built and tested based on the proposed scheme. The developed system detected, classified, and counted vehicles accurately. Moreover, the system also computes and provides the speed of the vehicle detected using a single set of multiple loops. The accuracy of the speed measurement has been compared with actual values and found to be accurate and can be used for real-time intelligent transportation system (ITS) applications under heterogeneous and less lane-disciplined (e.g., Indian) conditions.

The Cognitive Agent Architecture (Cougaar) is a distributed agent architecture framework originally developed to build large scale logistics applications for the Department of Defense. In order to facilitate rapid development of complex military and commercial Cougaar applications, we are devising "recipes" on how to automate the Cougaar application development process. The envisioned Cougaar Model Driven Architecture (CMDA) system will capture requirements from the user and automatically generate related software artifacts such as requirement, design, code and test cases. The automated generation of software artifacts, even if partial in nature, should considerably increase the productivity of Cougaar developers. Recognizing the sophistication of the Cougaar framework and the limitations of current transformation technologies, we have systematically developed an approach that combines component assembly in the large with transformations in the small. The approach’s ability to generate accurate software artifacts depends largely on how user requirements are captured and transformed. The CMDA system employs innovative approaches and techniques to enable users represent their requirements properly. This paper briefly describes the CMDA system, its user interface and the various inputs captured from the user.

Software development can be thought of as the evolution of abstract requirements into a concrete software system. The evolution, achieved through a successive series of transformations, is inherently a complex process. The inherent complexities, that often make these transformations sub-optimal, are further aggravated by inefficient capture and usage of requisite information during transformation. While some understanding of software may be reasonably clear at a given time, the future dependencies may not be fully understood or accessible. The clarifications obtained over time make the system more concretely understood, but there may be software information leaks (SILs) as some relevant information is lost. Some key SILs may be due to failure to be fully acquainted with dependencies between various software artifacts. In this paper, our objective is to define SILs as concept, codify an essential set of canonical leaks, and introduce solutions for dealing with some of them.