Consumer-grade range cameras such as the Kinect sensor have the potential to be used in mapping applications where accuracy requirements are less strict. To realize this potential insight into the geometric quality of the data acquired by the sensor is essential. In this paper we discuss the calibration of the Kinect sensor, and provide an analysis of the accuracy and resolution of its depth data. Based on a mathematical model of depth measurement from disparity a theoretical error analysis is presented, which provides an insight into the factors influencing the accuracy of the data. Experimental results show that the random error of depth measurement increases with increasing distance to the sensor, and ranges from a few millimeters up to about 4 cm at the maximum range of the sensor. The quality of the data is also found to be influenced by the low resolution of the depth measurements.
Iron(II) spin crossover molecular materials are made of coordination centres switchable between two states by temperature, pressure or a visible light irradiation. The relevant macroscopic parameter which monitors the magnetic state of a given solid is the high-spin (HS) fraction denoted nHS, i.e., the relative population of HS molecules. Each spin crossover material is distinguished by a transition temperature T-1/2 where 50% of active molecules have switched to the low-spin (LS) state. In strongly interacting systems, the thermal spin switching occurs abruptly at T-1/2. Applying pressure induces a shift from HS to LS states, which is the direct consequence of the lower volume for the LS molecule. Each material has thus a well defined pressure value P-1/2. In both cases the spin state change is easily detectable by optical means thanks to a thermo/piezochromic effect that is often encountered in these materials. In this contribution, we discuss potential use of spin crossover molecular materials as temperature and pressure sensors with optical detection. The ones presenting smooth transitions behaviour, which have not been seriously considered for any application, are spotlighted as potential sensors which should stimulate a large interest on this well investigated class of materials.
Appliance Load Monitoring (ALM) is essential for energy management solutions, allowing them to obtain appliance-specific energy consumption statistics that can further be used to devise load scheduling strategies for optimal energy utilization. Fine-grained energy monitoring can be achieved by deploying smart power outlets on every device of interest; however it incurs extra hardware cost and installation complexity. Non-Intrusive Load Monitoring (NILM) is an attractive method for energy disaggregation, as it can discern devices from the aggregated data acquired from a single point of measurement. This paper provides a comprehensive overview of NILM system and its associated methods and techniques used for disaggregated energy sensing. We review the state-of-the art load signatures and disaggregation algorithms used for appliance recognition and highlight challenges and future research directions.
Bluetooth Low Energy (BLE) is an emerging low-power wireless technology developed for short-range control and monitoring applications that is expected to be incorporated into billions of devices in the next few years. This paper describes the main features of BLE, explores its potential applications, and investigates the impact of various critical parameters on its performance. BLE represents a trade-off between energy consumption, latency, piconet size, and throughput that mainly depends on parameters such as connInterval and connSlaveLatency. According to theoretical results, the lifetime of a BLE device powered by a coin cell battery ranges between 2.0 days and 14.1 years. The number of simultaneous slaves per master ranges between 2 and 5,917. The minimum latency for a master to obtain a sensor reading is 676 mu s, although simulation results show that, under high bit error rate, average latency increases by up to three orders of magnitude. The paper provides experimental results that complement the theoretical and simulation findings, and indicates implementation constraints that may reduce BLE performance.
In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as finger print and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP) which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP).
This paper introduces the design and development of a novel pressure-sensitive foot insole for real-time monitoring of plantar pressure distribution during walking. The device consists of a flexible insole with 64 pressure-sensitive elements and an integrated electronic board for high-frequency data acquisition, pre-filtering, and wireless transmission to a remote data computing/storing unit. The pressure-sensitive technology is based on an optoelectronic technology developed at Scuola Superiore Sant'Anna. The insole is a low-cost and low-power battery-powered device. The design and development of the device is presented along with its experimental characterization and validation with healthy subjects performing a task of walking at different speeds, and benchmarked against an instrumented force platform.
User authentication in wireless sensor networks (WSN) is a critical security issue due to their unattended and hostile deployment in the field. Since sensor nodes are equipped with limited computing power, storage, and communication modules; authenticating remote users in such resource-constrained environments is a paramount security concern. Recently, M. L. Das proposed a two-factor user authentication scheme in WSNs and claimed that his scheme is secure against different kinds of attack. However, in this paper, we show that the M. L. Das-scheme has some critical security pitfalls and cannot be recommended for real applications. We point out that in his scheme: users cannot change/update their passwords, it does not provide mutual authentication between gateway node and sensor node, and is vulnerable to gateway node bypassing attack and privileged-insider attack. To overcome the inherent security weaknesses of the M. L. Das-scheme, we propose improvements and security patches that attempt to fix the susceptibilities of his scheme. The proposed security improvements can be incorporated in the M. L. Das-scheme for achieving a more secure and robust two-factor user authentication in WSNs.
We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system. A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations. For the static measurements, a plastic arm model simulating a human arm was used. A set of 37 reference locations was selected to cover the controller's sensory space. For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers. In the static scenario, the standard deviation was less than 0.5 mm. The linear correlation revealed a significant increase in the standard deviation when moving away from the controller. The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controller's surface. The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system.
Colorimetric sensing, which transduces environmental changes into visible color changes, provides a simple yet powerful detection mechanism that is well-suited to the development of low-cost and low-power sensors. A new approach in colorimetric sensing exploits the structural color of photonic crystals (PCs) to create environmentally-influenced color-changeable materials. PCs are composed of periodic dielectrics or metallo-dielectric nanostructures that affect the propagation of electromagnetic waves (EM) by defining the allowed and forbidden photonic bands. Simultaneously, an amazing variety of naturally occurring biological systems exhibit iridescent color due to the presence of PC structures throughout multi-dimensional space. In particular, some kinds of the structural colors in living organisms can be reversibly changed in reaction to external stimuli. Based on the lessons learned from natural photonic structures, some specific examples of PCs-based colorimetric sensors are presented in detail to demonstrate their unprecedented potential in practical applications, such as the detections of temperature, pH, ionic species, solvents, vapor, humidity, pressure and biomolecules. The combination of the nanofabrication technique, useful design methodologies inspired by biological systems and colorimetric sensing will lead to substantial developments in low-cost, miniaturized and widely deployable optical sensors.
We report on a new sensor strategy that integrates molecularly imprinted polymers (MIPs) with surface enhanced Raman scattering (SERS). The sensor was developed to detect the explosive, 2,4,6-trinitrotoluene (TNT). Micron thick films of sol gel-derived xerogels were deposited on a SERS-active surface as the sensing layer. Xerogels were molecularly imprinted for TNT using non-covalent interactions with the polymer matrix. Binding of the TNT within the polymer matrix results in unique SERS bands, which allow for detection and identification of the molecule in the MIP. This MIP-SERS sensor exhibits an apparent dissociation constant of (2.3 +/- 0.3) x 10(-5) M for TNT and a 3 mu M detection limit. The response to TNT is reversible and the sensor is stable for at least 6 months. Key challenges, including developing a MIP formulation that is stable and integrated with the SERS substrate, and ensuring the MIP does not mask the spectral features of the target analyte through SERS polymer background, were successfully met. The results also suggest the MIP-SERS protocol can be extended to other target analytes of interest.