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173 records · Page 10

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal

Bioinspired engineering of exploration systems for NASA and DoD

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers.

Space Flight

A strongly goal-directed close-range vision system for spacecraft docking

In this presentation, we will propose a strongly goal-oriented stereo vision system to establish proper docking approach motions for automated rendezvous and capture (AR&C). From an input sequence of stereo video image pairs, the system produces a current best estimate of: contact position; contact vector; contact velocity; and contact orientation. The processing demands imposed by this particular problem and its environment dictate a special case solution; such a system should necessarily be, in some sense, minimalist. By this we mean the system should construct a scene description just sufficiently rich to solve the problem at hand and should do no more processing than is absolutely necessary. In addition, the imaging resolution should be just sufficient. Extracting additional information and constructing higher level scene representations wastes energy and computational resources and injects an unnecessary degree of complexity, increasing the likelihood of malfunction. We therefore take a departure from most prior stereopsis work, including our own, and propose a system based on associative memory. The purpose of the memory is to immediately associate a set of motor commands with a set of input visual patterns in the two cameras. That is, rather than explicitly computing point correspondences and object positions in world coordinates and trying to reason forward from this information to a plan of action, we are trying to capture the essence of reflex behavior through the action of associative memory. The explicit construction of point correspondences and 3D scene descriptions, followed by online velocity and point of impact calculations, is prohibitively expensive from a computational point of view for the problem at hand. Learned patterns on the four image planes, left and right at two discrete but closely spaced instants in time, will be bused directly to infer the spacecraft reaction. This will be a continuing online process as the docking collar approaches.

Boyer, Kim L.

Atypical form of Alzheimer's disease with prominent posterior cortical atrophy: a review of lesion distribution and circuit disconnection in cortical visual pathways

In recent years, the existence of visual variants of Alzheimer's disease characterized by atypical clinical presentation at onset has been increasingly recognized. In many of these cases post-mortem neuropathological assessment revealed that correlations could be established between clinical symptoms and the distribution of neurodegenerative lesions. We have analyzed a series of Alzheimer's disease patients presenting with prominent visual symptomatology as a cardinal sign of the disease. In these cases, a shift in the distribution of pathological lesions was observed such that the primary visual areas and certain visual association areas within the occipito-parieto-temporal junction and posterior cingulate cortex had very high densities of lesions, whereas the prefrontal cortex had fewer lesions than usually observed in Alzheimer's disease. Previous quantitative analyses have demonstrated that in Alzheimer's disease, primary sensory and motor cortical areas are less damaged than the multimodal association areas of the frontal and temporal lobes, as indicated by the laminar and regional distribution patterns of neurofibrillary tangles and senile plaques. The distribution of pathological lesions in the cerebral cortex of Alzheimer's disease cases with visual symptomatology revealed that specific visual association pathways were disrupted, whereas these particular connections are likely to be affected to a less severe degree in the more common form of Alzheimer's disease. These data suggest that in some cases with visual variants of Alzheimer's disease, the neurological symptomatology may be related to the loss of certain components of the cortical visual pathways, as reflected by the particular distribution of the neuropathological markers of the disease.

Review

Retinal flow is sufficient for steering during observer rotation

How do people control locomotion while their eyes are simultaneously rotating? A previous study found that during simulated rotation, they can perceive a straight path of self-motion from the retinal flow pattern, despite conflicting extraretinal information, on the basis of dense motion parallax and reference objects. Here we report that the same information is sufficient for active control ofjoystick steering. Participants steered toward a target in displays that simulated a pursuit eye movement. Steering was highly inaccurate with a textured ground plane (motion parallax alone), but quite accurate when an array of posts was added (motion parallax plus reference objects). This result is consistent with the theory that instantaneous heading is determined from motion parallax, and the path of self-motion is determined by updating heading relative to environmental objects. Retinal flow is thus sufficient for both perceiving self-motion and controlling self-motion with a joystick; extraretinal and positional information can also contribute, but are not necessary.

Kinesthesis/physiology

Demonstration and Automation of Reflected Target Optical Measurement for Heliostats

Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. Since 2022, NREL has been developing a measurement method called the Reflected Target Non-intrusive Assessment (ReTNA) system. This system differs from most established methods in that we perform deflectometry with a pattern of coded targets, identified in space with photogrammetry. Reflected target systems have several advantages over traditional fringe deflectometry systems. Firstly, they can be operated in bright or ambient lighting, a challenge for fringe systems that use a projector and screen. Reflected target systems also can use a much lighter and less expensive target than projector-based systems. Lastly, 2D slope measurement can be solved from a single image, which leads to several advantages for accommodating faster measurements and smaller sized targets. These advantages make ReTNA particularly well-suited for applications where there are space or lighting constraints, like performing heliostat quality assurance on an assembly line. It's also useful when a lightweight, flexible system is needed, like for heliostat developers to quickly measure a new heliostat design at different orientations, to observe gravitational effects on the mirror surface shape. In the last year, significant improvements were made to this tool to make it more useful for these applications. These improvements were focused around validation of the ReTNA measurement system, and automation of the setup and measurement process. First, we present an improved ReTNA layout, for use on the heliostat assembly line. Next, we detail the various changes to the ReTNA software and computer vision methods to automate data collection in this new setup, and lessons learned from this process. The goal with this new setup is to perform a full heliostat surface characterization without removing the mirror from the assembly line. Lastly, we share results from several ReTNA validation studies undertaken over the last year. These include repeated ReTNA measurement on demonstration mirror facets, comparisons with other optical measurement tools, and some studies aimed at quantifying the uncertainty of ReTNA measurement under various constraints (mirror-target spacing, camera resolution, etc.). These results are compared with 2024 HelioCon performance targets, and our planned next steps for the ReTNA measurement system are presented.

CSP

Detection in fixed and random noise in foveal and parafoveal vision explained by template learning

Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.

NASA Center ARC

Path perception during rotation: influence of instructions, depth range, and dot density

How do observers perceive their direction of self-motion when traveling on a straight path while their eyes are rotating? Our previous findings suggest that information from retinal flow and extra-retinal information about eye movements are each sufficient to solve this problem for both perception and active control of self-motion [Vision Res. 40 (2000) 3873; Psych. Sci. 13 (2002) 485]. In this paper, using displays depicting translation with simulated eye rotation, we investigated how task variables such as instructions, depth range, and dot density influenced the visual system's reliance on retinal vs. extra-retinal information for path perception during rotation. We found that path errors were small when observers expected to travel on a straight path or with neutral instructions, but errors increased markedly when observers expected to travel on a curved path. Increasing depth range or dot density did not improve path judgments. We conclude that the expectation of the shape of an upcoming path can influence the interpretation of the ambiguous retinal flow. A large depth range and dense motion parallax are not essential for accurate path perception during rotation, but reference objects and a large field of view appear to improve path judgments.

Space Perception/physiology

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies

Luciola Hypertelescope Space Observatory

Luciola is a large (one kilometer) "multi-aperture densified-pupil imaging interferometer", or "hypertelescope" employing many small apertures, rather than a few large ones, for obtaining direct snapshot images with a high information content. A diluted collector mirror, deployed in space as a flotilla of small mirrors, focuses a sky image which is exploited by several beam-combiner spaceships. Each contains a pupil densifier micro-lens array to avoid the diffractive spread and image attenuation caused by the small sub-apertures. The elucidation of hypertelescope imaging properties during the last decade has shown that many small apertures tend to be far more efficient, regarding the science yield, than a few large ones providing a comparable collecting area. For similar underlying physical reasons, radio-astronomy has also evolved in the direction of many-antenna systems such as the proposed Low Frequency Array having hundreds of thousands of individual receivers . With its high limiting magnitude, reaching the mv=30 limit of HST when 100 collectors of 25cm will match its collecting area, high-resolution direct imaging in multiple channels, broad spectral coverage from the 1200 Angstrom ultra-violet to the 20 micron infra-red, apodization, coronagraphic and spectroscopic capabilities, the proposed hypertelescope observatory addresses very broad and innovative science covering different areas of ESA s Cosmic Vision program. In the initial phase, a focal spacecraft covering the UV to near IR spectral range of EMCCD photon-counting cameras ( currently 200 to 1000nm), will image details on the surface of many stars, as well as their environment, including multiple stars and clusters. Spectra will be obtained for each resel. It will also image neutron star, black-hole and micro-quasar candidates, as well as active galactic nuclei, quasars, gravitational lenses, and other Cosmic Vision targets observable with the initial modest crowding limit. With subsequent upgrade missions, the spectral coverage can be extended from 120nm to 20 microns, using four detectors carried by two to four focal spacecraft. The number of collector mirrors in the flotilla can also be increased from 12 to 100 and possibly 1,000. The imaging and spectroscopy of habitable exoplanets in the mid infra-red then becomes feasible once the collecting area reaches 6m2 , using a specialized mid infra-red focal spacecraft. Calculations ( Boccaletti et al., 2000) have shown that hypertelescope coronagraphy has unequalled sensitivity for detecting, at mid infra-red wavelengths, faint exoplanets within the exo-zodiacal glare. Later upgrades will enable the more difficult imaging and spectroscopy of these faint objects at visible wavelengths, using refined techniques of adaptive coronagraphy (Labeyrie. & Le Coroller, 2004). Together, the infra-red and visible spectral data carry rich information on the possible presence of life. The close environment of the central black-hole in the Milky Way will be imageable with unprecedented detail in the near infra-red . Cosmological imaging of remote galaxies at the limit of the known universe is also expected, from the ultra-violet to the near infra-red, following the first upgrade, and with greatly increasing sensitivity through successive upgrades. These areas will indeed greatly benefit from the upgrades, in terms of dynamic range, limiting complexity of the objects to be imaged, size of the elementary Direct Imaging Field , and limiting magnitude, approaching that of an 8-meter space telescope when 1000 apertures of 25cm are installed. Similar gains will occur for addressing fundamental problems in physics and cosmology, particularly when observing neutron stars and black holes, single or binary, including the giant black holes, with accretion disks and jets, in active galactic nuclei beyond the Milky Way. Gravitational lensing and micro-lensing patterns, including time-variable patterns and perhaps millisecond lensing flasheshich may be beamed by diffraction from sub-stellar masses at sub-parsec distances (Labeyrie, 1994) , will also be observable initially in the favourable cases, and upgrades will greatly improve the number of observable objects. The observability of gravitational waves emitted by binary lensing masses, in the form of modulated lensing patterns, is a debated issue ( Ragazzoni et al., 2003) but will also become addressable observationally. The technology readiness of Luciola approaches levels where low-orbit testing and stepwise implementation will become feasible in the 2015-2025 time frame. For the following decades beyond 2020, once accurate formation flying techniques will be mastered, much larger hypertelescopes such as the proposed 100km Exo-Earth Imager and the 100,000 km Neutron Star Imager should also become feasible. Luciola is therefore also seen as a precursor toward such very powerful instruments.

Labeyrie, Antoine

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob