Model Based Target Tracking in a Wireless Network of Passive Infrared Sensor Nodes

We consider the problem of tracking an intruder in a plane region by using a wireless sensor network comprising motes equipped with passive infrared (PIR) sensors deployed over the region. An input-output model for the PIR sensor and a method to estimate the angular speed of the target from the sensor output are proposed. With the measurement model so obtained, we study the centralized and decentralized tracking performance using the extended Kalman filter.

A touchless passive Infrared gesture sensor.

A sensing device for a touchless, hand gesture, user interface based on an inexpensive passive infrared pyroelectric detector array is presented. The 2 x 2 element sensor responds to changing infrared radiation generated by hand movement over the array. The sensing range is from a few millimetres to tens of centimetres. The low power consumption (< 50 μW) enables the sensor’s use in mobile devices and in low energy applications. Detection rates of 77% have been demonstrated using a prototype system that differentiates the four main hand motion trajectories – up, down, left and right. This device allows greater non-contact control capability without an increase in size, cost or power consumption over existing on/off devices.

Predicting room occupancy with a single passive infrared (PIR) sensor through behavior extraction

Passive infrared sensors have widespread use in many applications, including motion detectors for alarms, lighting systems and hand dryers. Combinations of multiple PIR sensors have also been used to count the number of humans passing through doorways. In this paper, we demonstrate the potential of the PIR sensor as a tool for occupancy estimation inside of a monitored environment. Our approach shows how flexible nonparametric machine learning algorithms extract useful information about the occupancy from a single PIR sensor. The approach allows us to understand and make use of the motion patterns generated by people within the monitored environment. The proposed counting system uses information about those patterns to provide an accurate estimate of room occupancy which can be updated every 30 seconds. The system was successfully tested on data from more than 50 real office meetings consisting of at most 14 room occupants.

Trace gas measurements from infrared satellite for chemistry and climate applications

Space-borne thermal infrared instruments working in the nadir geometry are providing spectroscopic measurements of species that impact on the chemical composition of the atmosphere and on the climate forcing: H2O, CO2, N2O, CH4, CFCs, O3, and CO. The atmospheric abundances obtained from the analysis of IMG/ADEOS measurements are discussed in order to demonstrate the potential scientific return to be expected from future missions using advanced infrared nadir sounders. Some strengths and limitations of passive infrared remote sensing from space are illustrated. © 2003 European Geosciences Union.

Infrared Thermography Enhancements for Concrete Bridge Evaluation

Infrared thermography is a well-recognized non-destructive testing technique for evaluating concrete bridge elements such as bridge decks and piers. However, overcoming some obstacles and limitations are necessary to be able to add this invaluable technique to the bridge inspector's tool box. Infrared thermography is based on collecting radiant temperature and presenting the results as a thermal infrared image. Two methods considered in conducting an infrared thermography test include passive and active. The source of heat is the main difference between these two approaches of infrared thermography testing. Solar energy and ambient temperature change are the main heat sources in conducting a passive infrared thermography test, while active infrared thermography involves generating a temperature gradient using an external source of heat other than sun. Passive infrared thermography testing was conducted on three concrete bridge decks in Michigan. Ground truth information was gathered through coring several locations on each bridge deck to validate the results obtained from the passive infrared thermography test. Challenges associated with data collection and processing using passive infrared thermography are discussed and provide additional evidence to confirm that passive infrared thermography is a promising remote sensing tool for bridge inspections. To improve the capabilities of the infrared thermography technique for evaluation of the underside of bridge decks and bridge girders, an active infrared thermography technique using the surface heating method was developed in the laboratory on five concrete slabs with simulated delaminations. Results from this study demonstrated that active infrared thermography not only eliminates some limitations associated with passive infrared thermography, but also provides information regarding the depth of the delaminations. Active infrared thermography was conducted on a segment of an out-of-service prestressed box beam and cores were extracted from several locations on the beam to validate the results. This study confirms the feasibility of the application of active infrared thermography on concrete bridges and of estimating the size and depth of delaminations. From the results gathered in this dissertation, it was established that applying both passive and active thermography can provide transportation agencies with qualitative and quantitative measures for efficient maintenance and repair decision-making.

RFID based Efficient Lighting Control

The Kyoto Protocol and the European Energy Performance of Buildings Directive put an onus on governments
and organisations to lower carbon footprint in order to contribute towards reducing global warming. A key
parameter to be considered in buildings towards energy and cost savings is its indoor lighting that has a major
impact on overall energy usage and Carbon Dioxide emissions. Lighting control in buildings using Passive
Infrared sensors is a reliable and well established approach; however, the use of only Passive Infrared does not
offer much savings towards reducing carbon, energy, and cost. Accurate occupancy monitoring information can
greatly affect a building’s lighting control strategy towards a greener usage. This paper presents an approach for
data fusion of Passive Infrared sensors and passive Radio Frequency Identification (RFID) based occupancy
monitoring. The idea is to have efficient, need-based, and reliable control of lighting towards a green indoor
environment, all while considering visual comfort of occupants. The proposed approach provides an estimated
13% electrical energy savings in one open-plan office of a University building in one working day. Practical
implementation of RFID gateways provide real-world occupancy profiling data to be fused with Passive
Infrared sensing towards analysis and improvement of building lighting usage and control.

Camera traps : the research paparazzi

The use of cameras to monitor wildlife is commonplace; however, little is known of the effectiveness of different camera technologies for the detection of mammals. We compared the detection success of three different camera systems, a passive infrared (IR) system, an active IR and a constant video camera, alongside a trapping grid of Elliott and cage traps to determine their effectiveness at detecting mammals at multiple locations in the Otways National Park, Victoria, Australia (n = 160 events; 40 ± 23 [SD] events per night). Species detected and detection rates differed between methods (χ2 = 57.95, df = 2, p < 0.0001). Only house mice (Mus musculus) were detected by camera and traditional trapping techniques. Camera systems alone detected foxes (Vulpes vulpes) and a koala (Phascolarctos cinereus), while traditional traps captured bush rats (Rattus fuscipes), agile antechinus (Antechinus agilis) and a brush-tailed possum (Trichosurus vulpecula) which were not detected by the camera systems. Assuming that the video camera detected all mammals at the camera trap, the passive IR system detected almost all mammals detected by the video and it detected significantly more species than the active IR system. The choice of method will ultimately depend on the species of interest, logistics and the study site, and may substantially influence the results of a study.

Evaluation of three remote camera systems for detecting mammals and birds

Automated camera systems have widespread application in wildlife studies and their use is increasing (Kucera & Barrett 1993; Cutler & Swann 1999; Swann et al. 2004; Parker et al. 2008). Among other applications, they have been used to produce species inventories, estimate population sizes, study behaviour and examine the impact and activity of predators (Cutler & Swann 1999; Swann et al. 2004). Modern camera systems can operate for extended durations, are relatively non-invasive, easy to operate, portable, durable and can take good-quality images by day and night (Kucera & Barrett 1993; Peterson & Thomas 1998; Allison & Destefano 2006; Parker et al. 2008). Beyond their scientific applications, the generation of high-quality images can be useful for educational and conservation purposes (Cutler & Swann 1999). The two most common types of systems currently used in ecological research are passive and active infrared (IR) systems (Cutler & Swann 1999; Parker et al. 2008). An older form of remote photography is video which captures a continuous record of activity at a focal site (Stewart et al.1997; King et al. 2001). Camera systems have certain limitations and biases (Swann et al. 2004), yet these have not been well studied. Refinement of the use of camera systems is required to fully realize their value (Towerton et al. 2008). Here, we describe a comparison of detection rates of mammals and birds by passive and active IR camera systems, using a video system to benchmark detection rates.

Can camera traps monitor Komodo dragons a large ectothermic predator?

Camera trapping has greatly enhanced population monitoring of often cryptic and low abundance apex carnivores. Effectiveness of passive infrared camera trapping, and ultimately population monitoring, relies on temperature mediated differences between the animal and its ambient environment to ensure good camera detection. In ectothermic predators such as large varanid lizards, this criterion is presumed less certain. Here we evaluated the effectiveness of camera trapping to potentially monitor the population status of the Komodo dragon (Varanus komodoensis), an apex predator, using site occupancy approaches. We compared site-specific estimates of site occupancy and detection derived using camera traps and cage traps at 181 trapping locations established across six sites on four islands within Komodo National Park, Eastern Indonesia. Detection and site occupancy at each site were estimated using eight competing models that considered site-specific variation in occupancy (ψ)and varied detection probabilities (p) according to detection method, site and survey number using a single season site occupancy modelling approach. The most parsimonious model [ψ (site), p (site survey); ω = 0.74] suggested that site occupancy estimates differed among sites. Detection probability varied as an interaction between site and survey number. Our results indicate that overall camera traps produced similar estimates of detection and site occupancy to cage traps, irrespective of being paired, or unpaired, with cage traps. Whilst one site showed some evidence detection was affected by trapping method detection was too low to produce an accurate occupancy estimate. Overall, as camera trapping is logistically more feasible it may provide, with further validation, an alternative method for evaluating long-term site occupancy patterns in Komodo dragons, and potentially other large reptiles, aiding conservation of this species.

Caracterização do ritmo de atividade/repouso do Mocó (Kerodon Rupestris) em fotoperíodo artificial

Kerodon rupestris (rock cavy, mocó) is an endemic caviidae of Brazilian northeast that inhabits rocky places in the semi arid region. The aim of this study was to characterize the activity/rest rhythm of the rock cavy under 12:12 h LD cycle and continuous light. In the first stage, seven animals were submitted to two light intensities (LD; 250:0 lux and 400:0 lux; 40 days each intensity). In the second stage four males were kept for 40 days in LD (470:<1 lux), for 18 days in LL 470 lux (LL470) and for 23 days in red dim light below 1 lux (LL<1). In the third stage three males were initially kept in LD 12:12 h (450:<1 lux) and after that in LL with gradual increase in light intensity each 21 days (<1 lux LL<1; 10 lux-LL10; 160 lux LL160; 450 lux LL450). In the fourth stage it was analyzed the motor activity of 16 animals in the first 10 days in LD. Motor activity was continuously recorded by passive infrared movement sensors connected to a computer and totaled in 5 min bins. The activity showed circadian and ultradian rhythms and activity peaks at phase transitions. The activity and the rest occurred in the light as well as in the dark phase, with activity mean greater in the light phase for most of the animals. The light intensity influenced the activity/rest rhythm in the first three stages and in the first stage the activity in 400 lux increased in four animals and decreases in two. In the second stage, the tau for 3 animals in LL470 was greater than 24 h; in LL<1 it was greater than 24 h for one and lower for two. In the third stage the tau decreased with the light intensity increase for animal 8. During the first days in the experimental room, the animals did not synchronize to the LD cycle with activity and rest occurring in both phases. The results indicate that the activity/rest rhythm of Kerodon rupestris can be affected by light intensity and that the synchronization to the LD cycle results from entrainment as well as masking probably as a consequence of the action of two or more oscillators with low coupling strength

Influência de fotoperíodo artificial no comportamento de um primata neotropical diurno (Callithrix jacchus)

One of the main environmental cues for the adjustment of temporal organization of the animals is the light-dark cycle (LD), which undergoes changes in phase duration throughout the seasons. Photoperiod signaling by melatonin in mammals allows behavioral changes along the year, as in the activity-rest cycle, in mood states and in cognitive performance. The aim of this study was to investigate if common marmoset (Callithrix jacchus) exhibits behavioral changes under short and long photoperiods in a 24h cycle, assessing their individual behaviors, vocal repertoire, exploratory activity (EA), recognition memory (RM) and the circadian rhythm of locomotor activity (CRA). Eight adult marmosets were exposed to a light-dark cycle of 12:12; LD 08:16; LD 12:12 and LD 16:08, sequentially, for four weeks in each condition. Locomotor activity was recorded 24h/day by passive infrared motion detectors above the individual cages. A video camera system was programmed to record each animal, twice a week, on the first two light hours. From the videos, frequency of behaviors was registered as anxiety-like, grooming, alert, hanging position, staying in nest box and feeding using continuous focal animal sampling method. Simultaneously, the calls emitted in the experimental room were recorded by a single microphone centrally located and categorized as affiliative (whirr, chirp), contact (phee), long distance (loud shrill), agonistic (twitter) and alarm (tsik, seep, see). EA was assessed on the third hour after lights onset on the last week of each condition. In a first session, marmosets were exposed to one unfamiliar object during 15 min and 24h later, on the second session, a novel object was added to evaluate RM. Results showed that long days caused a decreased of amplitude and period variance of the CRA, but not short days. Short days decreased the total daily activity and active phase duration. On long days, active phase duration increased due to an advance of activity onset in relation to symmetric days. However, not all subjects started the activity earlier on long days. The activity offset was similar to symmetric days for the majority of marmosets. Results of EA showed that RM was not affected by short or long days, and that the marmosets exhibited a decreased in duration of EA on long days. Frequency and type of calls and frequency of anxiety-like behaviors, staying in nest box and grooming were lower on the first two light hours on long days. Considering the whole active phase of marmosets as we elucidate the results of vocalizations and behaviors, it is possible that these changes in the first two light hours are due to the shifting of temporal distribution of marmoset activities, since some animals did not advance the activity onset on long days. Consequently, the marmosets mean decreased because the sampling was not possible. In conclusion, marmosets synchronized the CRA to the tested photoperiods and as the phase angle varied a lot among marmosets it is suggested that they can use different strategies. Also, long days had an effect on activity-rest cycle and exploratory behaviors

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Deep near-infrared spectroscopy of high-redshift galaxies: the physical growth of passive systems

The assembly history of massive galaxies is one of the most important aspects of galaxy formation and evolution. Although we have a broad idea of what physical processes govern the early phases of galaxy evolution, there are still many open questions. In this thesis I demonstrate the crucial role that spectroscopy can play in a physical understanding of galaxy evolution. I present deep near-infrared spectroscopy for a sample of high-redshift galaxies, from which I derive important physical properties and their evolution with cosmic time. I take advantage of the recent arrival of efficient near-infrared detectors to target the rest-frame optical spectra of z > 1 galaxies, from which many physical quantities can be derived. After illustrating the applications of near-infrared deep spectroscopy with a study of star-forming galaxies, I focus on the evolution of massive quiescent systems.

Most of this thesis is based on two samples collected at the W. M. Keck Observatory that represent a significant step forward in the spectroscopic study of z > 1 quiescent galaxies. All previous spectroscopic samples at this redshift were either limited to a few objects, or much shallower in terms of depth. Our first sample is composed of 56 quiescent galaxies at 1 < z < 1.6 collected using the upgraded red arm of the Low Resolution Imaging Spectrometer (LRIS). The second consists of 24 deep spectra of 1.5 < z < 2.5 quiescent objects observed with the Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE). Together, these spectra span the critical epoch 1 < z < 2.5, where most of the red sequence is formed, and where the sizes of quiescent systems are observed to increase significantly.

We measure stellar velocity dispersions and dynamical masses for the largest number of z > 1 quiescent galaxies to date. By assuming that the velocity dispersion of a massive galaxy does not change throughout its lifetime, as suggested by theoretical studies, we match galaxies in the local universe with their high-redshift progenitors. This allows us to derive the physical growth in mass and size experienced by individual systems, which represents a substantial advance over photometric inferences based on the overall galaxy population. We find a significant physical growth among quiescent galaxies over 0 < z < 2.5 and, by comparing the slope of growth in the mass-size plane dlogR_e/dlogM_∗ with the results of numerical simulations, we can constrain the physical process responsible for the evolution. Our results show that the slope of growth becomes steeper at higher redshifts, yet is broadly consistent with minor mergers being the main process by which individual objects evolve in mass and size.

By fitting stellar population models to the observed spectroscopy and photometry we derive reliable ages and other stellar population properties. We show that the addition of the spectroscopic data helps break the degeneracy between age and dust extinction, and yields significantly more robust results compared to fitting models to the photometry alone. We detect a clear relation between size and age, where larger galaxies are younger. Therefore, over time the average size of the quiescent population will increase because of the contribution of large galaxies recently arrived to the red sequence. This effect, called progenitor bias, is different from the physical size growth discussed above, but represents another contribution to the observed difference between the typical sizes of low- and high-redshift quiescent galaxies. By reconstructing the evolution of the red sequence starting at z ∼ 1.25 and using our stellar population histories to infer the past behavior to z ∼ 2, we demonstrate that progenitor bias accounts for only half of the observed growth of the population. The remaining size evolution must be due to physical growth of individual systems, in agreement with our dynamical study.

Finally, we use the stellar population properties to explore the earliest periods which led to the formation of massive quiescent galaxies. We find tentative evidence for two channels of star formation quenching, which suggests the existence of two independent physical mechanisms. We also detect a mass downsizing, where more massive galaxies form at higher redshift, and then evolve passively. By analyzing in depth the star formation history of the brightest object at z > 2 in our sample, we are able to put constraints on the quenching timescale and on the properties of its progenitor.

A consistent picture emerges from our analyses: massive galaxies form at very early epochs, are quenched on short timescales, and then evolve passively. The evolution is passive in the sense that no new stars are formed, but significant mass and size growth is achieved by accreting smaller, gas-poor systems. At the same time the population of quiescent galaxies grows in number due to the quenching of larger star-forming galaxies. This picture is in agreement with other observational studies, such as measurements of the merger rate and analyses of galaxy evolution at fixed number density.

Ad hoc radiometric calibration of a thermal-infrared camera

Many applications can benefit from the accurate surface temperature estimates that can be made using a passive thermal-infrared camera. However, the process of radiometric calibration which enables this can be both expensive and time consuming. An ad hoc approach for performing radiometric calibration is proposed which does not require specialized equipment and can be completed in a fraction of the time of the conventional method. The proposed approach utilizes the mechanical properties of the camera to estimate scene temperatures automatically, and uses these target temperatures to model the effect of sensor temperature on the digital output. A comparison with a conventional approach using a blackbody radiation source shows that the accuracy of the method is sufficient for many tasks requiring temperature estimation. Furthermore, a novel visualization method is proposed for displaying the radiometrically calibrated images to human operators. The representation employs an intuitive coloring scheme and allows the viewer to perceive a large variety of temperatures accurately.

Evaluation of a Passive Millimeter Wave (PMMW) imager for wire detection in degraded visual conditions

Ground vehicle tests have been performed to evaluate the performance of a Passive Millimeter Wave (PMMW) imager in reduced visibility conditions and in particular, the ability to detect power lines and cables. A PMMW imager was
compared with Long Wave Infrared (LWIR) and visible imaging cameras. The three sensors were mounted on a Land Rover, together with GPS and digital recording system. All three sensors plus the GPS data were recorded simultaneously in order to provide direct comparisons. The vehicle collected imagery from a number of sites in the vicinity of Malvern, UK, in January, 2008. Imagery was collected both while the vehicle was stationary at specific sites
and while it was moving. Weather conditions during the data collection included clear, drizzle, rain and fog. Imagery was collected during the day, at night, and during dusk/dawn transition periods. The PMMW imager was a prototype which operated at 94 GHz and was based on a conically scanned folded Schmidt camera and the LWIR and visible sensors were commercial off the shelf items.