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DOE OSTI2025

Light-powered end-to-end neutron detection and imaging with an edge-deployed optical AI chip

Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗
NASA NTRS1970

Investigation of an Optimum Detection Scheme for a Star-Field Mapping System

An investigation was made to determine the optimum detection scheme for a star-field mapping system that uses coded detection resulting from starlight shining through specially arranged multiple slits of a reticle. The computer solution of equations derived from a theoretical model showed that the greatest probability of detection for a given star and background intensity occurred with the use of a single transparent slit. However, use of multiple slits improved the system's ability to reject the detection of undesirable lower intensity stars, but only by decreasing the probability of detection for lower intensity stars to be mapped. Also, it was found that the coding arrangement affected the root-mean-square star-position error and that detection is possible with error in the system's detected spin rate, though at a reduced probability.

Aldridge, M. D.↗
NASA NTRS1974

Inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Disturbances in a forest environment that cause reductions in forest area, timber volume, and timber growth can be detected on ERTS-1 combined color composites. However, detection depends on comparing a conventional aerial photograph taken at some base year with an ERTS-1 image taken in some subsequent year. In a test made on the Atlanta site, 1:63,360 scale aerial photo index sheets made in 1966 were compared with ERTS-1 image 1264-15445 (April 1973). Five factors were found important to detection reliability: (1) the quality of the imagery; (2) the season of the imagery; (3) the size of the disturbed area; (4) the number of years since the disturbances; and (5) the type of cutting treatment. Of 209 disturbances verified on aerial photography, 165 (or approximately 80%) were detected on the ERTS-1 image by one independent interpreter. Improved training and additional experience in using this low resolution imagery should improve detection. Of the two seasons of data studies (fall and early spring), early spring is the best for detecting land use changes. Generally speaking, winter, early spring, and early summer are the best times of year for detecting forest disturbances.

Heller, R. C.↗
NASA NTRS1977

The effects of participatory mode and task workload on the detection of dynamic system failures

The ability of operators to detect step changes in the dynamics of control systems is investigated as a joint function of, (1) participatory mode: whether subjects are actively controlling those dynamics or are monitoring an autopilot controlling them, and (2) concurrent task workload. A theoretical analysis of detection in the two modes identifies factors that will favor detection in either mode. Three subjects detected system failures in either an autopilot or manual controlling mode, under single-task conditions and concurrently with a subcritical tracking task. Latency and accuracy of detection were assessed and related through a speed accuracy tradeoff representation. It was concluded that failure detection performance was better during manual control than during autopilot control, and that the extent of this superiority was enhanced as dual-task load increased. Ensemble averaging and multiple regression techniques were then employed to investigate the cues utilized by the subjects in making their detection decisions.

Wickens, C. D.↗
NASA NTRS1986

Geostationary microwave imagers detection criteria

Geostationary orbit is investigated as a vantage point from which to sense remotely the surface features of the planet and its atmosphere, with microwave sensors. The geometrical relationships associated with geostationary altitude are developed to produce an efficient search pattern for the detection of emitting media and metal objects. Power transfer equations are derived from the roots of first principles and explain the expected values of the signal-to-clutter ratios for the detection of aircraft, ships, and buoys and for the detection of natural features where they are manifested as cold and warm eddies. The transport of microwave power is described for modeled detection where the direction of power flow is explained by the Zeroth and Second Laws of Thermodynamics. Mathematical expressions are derived that elucidate the detectability of natural emitting media and metal objects. Signal-to-clutter ratio comparisons are drawn among detectable objects that show relative detectability with a thermodynamic sensor and with a short-pulse radar.

Stacey, J. M.↗
NASA NTRS1987

A vector-based failure detection and isolation algorithm for a dual fail-operational redundant strapdown inertial measurement unit

A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.

Morrell, Frederick R.↗
NASA NTRS1992

Comparison of edges detected at different polarisations in MAESTRO data

Edge detection would appear to be a crucial tool for analyzing multi-polarized, multi-frequency, and multi-temporal Synthetic Aperture Radar (SAR) images. Edge structure provides a simple means for comparing different polarizations and frequencies, and for detecting changes over time. Due to the fact that edges and segments (homogeneous regions) are dual concepts, edge detection has an important role to play in identifying segments within which mean backscatter measurements for use in image classification can be made. As part of a general investigation into edge detection in SAR imagery, an initial investigation was carried out into the detectability and nature of edges in multi-polarized and multi-frequency SAR images. The contrast ratio (CR) operator was used to detect edges. This operator was previously shown to perform well at detecting edges in single-polarized and single-frequency SAR images.

Caves, Ronald G.↗
NASA NTRS1995

Hubble Space Telescope Images of Nearby Luminous Quasars: Results for Eight Quasars and Tests of the Detection Sensitivity - 2

Observations with the Wide-Field Camera of the Hubble Space Telescope (HST) are presented for eight intrinsically luminous quasars with redshifts between 0.16 and 0.29. These observations, when combined with a similar HST study of the quasar PKS 2349-014, show that luminous nearby quasars exist in a variety of environments. Seven companion galaxies brighter than M(V) = 16.5 (H(sub 0) = 100 km s(sup -1) Mpc(sup -1), Omega(sub 0) = 1.0) lie within a projected distance of 25 kpc of the quasars; three of the companions are located closer than 3'' (6 kpc projected distance) from the quasars, well within the volume that would be enclosed by a typical L* host galaxy. The observed association of quasars and companion galaxies is statistically significant and may he an important element in the luminous-quasar phenomenon. Apparent host galaxies are detected for three of the quasars: PG 1116+215, 3C 273, and PG 1444+407; the hosts have an average absolute magnitude of about 0.6 mag brighter than L*. The agreement between the previously published major-axis directions in ground-based images and in the present HST images of 3C 273 and PG 1444+407 constitutes important evidence supporting the reality of these candidate host galaxies. Upper limits are placed on the visual-band brightnesses of representative galactic hosts for all the quasars. These limits are established by placing galaxy images obtained with HST underneath the quasars and measuring at what faintness level the known galaxies are detected. On average, the HST spirals would have been detected if they were as faint as 1 mag below L*, and the early-type galaxies could have been detected down to a brightness level of about L*, where L* is the Schechter characteristic luminosity of field galaxies. Smooth, featureless galaxy models (exponential disks or de Vaucouleurs profiles) are fitted to the residual light after a best-fitting point source is subtracted from the quasar images. The results show that smooth spiral galaxies brighter than, on average, about L*, would have been detected. These upper limits, or possible detections, are consistent with, for example, the eight luminous quasars studied in this paper, occurring in host galaxies that have a Shechter luminosity function with a lower cutoff in the range 0.01-0.1 L*. Tests are performed to determine if our failure to detect, in some cases, luminous host galaxies could be an artifact caused by our analysis procedures. These tests include comparing the measured point-spread function (PSF) for our HST observations with the PSFs used in previous ground-based studies of host galaxies, measuring the fluctuations in the sky signals that were subtracted from the quasar images, evaluating empirically the effects of using different stellar PSFs in the analysis, carrying out the subtraction of the stellar (nuclear) source in different ways, creating and analyzing artificial active galactic nuclei (AGNs) with known surface brightnesses, and fitting the observed quasar light to an analytic model that includes a host galaxy.

Bahcall, John N.↗
NASA NTRS1997

Detection of Obstacles in Monocular Image Sequences

The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image.

Kasturi, Rangachar↗
NASA NTRS2001

Detection of Soluble and Fixed NH4+ in Clay Minerals by DTA and IR Reflectance Spectroscopy : A Potential Tool for Planetary Surface Exploration

Nitrogen is an essential element for life. It is the only element among the six major biogenic elements, C, O, S, O, P, H, whose presence in the Martian soil has not been positively and directly established. We describe here a study assessing the ability to detect NH4 in soils by two methods: differential thermal analysis (DTA) and infrared (IR) reflectance spectroscopy. Four standard clay minerals (kaolinite, montmorillonite, illite and attapulgite) and an altered tephra sample from Mauna Kea were treated with NH4 in this study. Samples of the NH4-treated and leached clays were analyzed by DTA and infrared (IR) reflectance spectroscopy to quantify the delectability of soluble and sorbed/fixed NH4. An exotherm at 270-280 C was clearly detected in the DTA curves of NH4-treated (non-leached) samples. This feature is assigned to the thermal decomposition reaction of NH4. Spectral bands observed at 1.56, 2.05, 2.12, 3.06, 3.3, 3.5, 5.7 and 7.0 microns in the reflectance spectra of NH4-treated and leached samples are assigned to the sorbed/fixed ammonium in the clays. The montmorillonite has shown the most intense absorbance due to fixed ammonium among the leached samples in this study, as a result of its high cation sorption capacity. It is concluded that the presence of sorbed or fixed NH4 in clays may be detected by infrared (IR) reflectance or emission spectroscopy. Distinction between soluble and sorbed NH4 may be achieved through the presence or absence of several spectral features assigned to the sorbed NH4 moietyi and, specifically, by use of the 4.2 micrometer feature assigned to solution NH4. Thermal analyses furnish supporting evidence of ammonia in our study through detection of N released at temperatures of 270-330 C. Based on these results it is estimated that IR spectra measured from a rover should be able to detect ammonia if present above 20 mg NH4/g sample in the surface layers. Orbital IR spectra and thermal analyses measured on a rover may be able to detect ammonia in soils as well but at higher abundances. The spectral features at 3.06 and 7.0 microns due to bound NH4 in clays and altered Hawaiian tephra appear to be the most promising for detection by orbital spectrometers. If N species are present on Mars the sedimentary deposits may be the best regions to look for them.

Janice, Bishop↗
NASA NTRS2002

Wire Detection Algorithms for Navigation

In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. Two approaches were explored for this purpose. The first approach involved a technique for sub-pixel edge detection and subsequent post processing, in order to reduce the false alarms. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter. The second approach involved the use of an example-based learning scheme namely, Support Vector Machines. The purpose of this approach was to explore the feasibility of an example-based learning based approach for the task of detecting wires from their images. Support Vector Machines (SVMs) have emerged as a promising pattern classification tool and have been used in various applications. It was found that this approach is not suitable for very thin wires and of course, not suitable at all for sub-pixel thick wires. High dimensionality of the data as such does not present a major problem for SVMs. However it is desirable to have a large number of training examples especially for high dimensional data. The main difficulty in using SVMs (or any other example-based learning method) is the need for a very good set of positive and negative examples since the performance depends on the quality of the training set.

Kasturi, Rangachar↗
NASA NTRS1999

Detection of endogenous alkaline phosphatase activity in intact cells by flow cytometry using the fluorogenic ELF-97 phosphatase substrate

BACKGROUND: The alkaline phosphatase (AP) substrate 2-(5'-chloro-2'-phosphoryloxyphenyl)-6-chloro-4-(3H)-quinazolinone (ELF((R))-97 for enzyme-labeled fluorescence) has been found useful for the histochemical detection of endogenous AP activity and AP-tagged proteins and oligonucleotide probes. In this study, we evaluated its effectiveness at detecting endogenous AP activity by flow cytometry. METHODS: The ELF-97 phosphatase substrate was used to detect endogenous AP activity in UMR-106 rat osteosarcoma cells and primary cultures of chick chondrocytes. Cells were labeled with the ELF-97 reagent and analyzed by flow cytometry using an argon ultraviolet (UV) laser. For comparison purposes, cells were also assayed for AP using a Fast Red Violet LB azo dye assay previously described for use in detecting AP activity by flow cytometry. RESULTS: The ELF-97 phosphatase substrate effectively detected endogenous AP activity in UMR-106 cells, with over 95% of the resulting fluorescent signal resulting from AP-specific activity (as determined by levamisole inhibition of AP activity). In contrast, less than 70% of the fluorescent signal from the Fast Red Violet LB (FRV) assay was AP-dependent, reflecting the high intrinsic fluorescence of the unreacted components. The ELF-97 phosphatase assay was also able to detect very low AP activity in chick chondrocytes that was undetectable by the azo dye method. CONCLUSIONS: The ELF-97 phosphatase assay was able to detect endogenous AP activity in fixed mammalian and avian cells by flow cytometry with superior sensitivity to previously described assays. This work also shows the applicability of ELF-97 to flow cytometry, supplementing its previously demonstrated histochemical applications. Copyright 1999 Wiley-Liss, Inc.

Non-NASA Center↗
NASA NTRS2004

Detecting Organic Compounds in Martian Soil Analogues Using Gas Chromatography Mass Spectrometry

One of the primary objectives of the 1976 Viking missions was to determine whether organic compounds, possibly of biological origin, were present in the Martian surface soils. The Viking gas chromatography mass spectrometry (GCMS) instruments found no evidence for any organic compounds of Martian origin above a few parts per billion in the upper 10 cm of surface soil [l], suggesting the absence of a widely distributed Martian biota. However, Benner et d. have suggested that significant amounts of non-volatile organic compounds, possibly including oxidation products of bioorganic molecules (e.g. carboxylic acids) would not have been detected by the Viking GCMS [2]. Moreover, other key organic compounds important to biology, such as amino acids and nucleobases, would also likely have been missed by the Viking GCMS as these compounds require chemical derivatization to be stable in a GC column [3]. Recent pyrolysis experiments with a Mars soil analogue that had been innoculated with Escherichia coli bacteria have shown that amino acid decomposition products (amines) and nucleobases are among the most abundant products generated after pyrolysis of the bacterial cells [4,5]. At the part per billion level (Viking GCMS detection limit), these pyrolysis products generated from several million bacterial cells per gram of Martian soil would not have been detected by the Viking GCMS instruments [4]. Analytical protocols are under development for upcoming in situ lander opportunities to target several important biological compounds including amino acids and nucleobases. For example, extraction and chemical derivatization techniques [3] are being adapted for space flight use to transform reactive or fragile molecules that would not have been detected by the Viking GCMS instruments, into species that are sufficiently volatile to be detected by GCMS. Recent experiments carried out at NASA Goddard have shown that using this derivatization technique all of the targeted compounds mentioned above can be separated on a GC column and detected by MS at sub-picomole (< 10(exp -l2 mole) levels. With these methods, the detection limit for amino acids, carboxylic acids and nucleobases is several orders of magnitude more sensitive than the Viking GCMS instruments for these compounds. Preliminary results using this analytical technique on a variety of Martian soil analogues will be presented.

Glavin, D. P.↗
NASA NTRS2003

Improved Conflict Detection for Reducing Operational Errors in Air Traffic Control

An operational error is an incident in which an air traffic controller allows the separation between two aircraft to fall below the minimum separation standard. The rates of such errors in the US have increased significantly over the past few years. This paper proposes new detection methods that can help correct this trend by improving on the performance of Conflict Alert, the existing software in the Host Computer System that is intended to detect and warn controllers of imminent conflicts. In addition to the usual trajectory based on the flight plan, a "dead-reckoning" trajectory (current velocity projection) is also generated for each aircraft and checked for conflicts. Filters for reducing common types of false alerts were implemented. The new detection methods were tested in three different ways. First, a simple flightpath command language was developed t o generate precisely controlled encounters for the purpose of testing the detection software. Second, written reports and tracking data were obtained for actual operational errors that occurred in the field, and these were "replayed" to test the new detection algorithms. Finally, the detection methods were used to shadow live traffic, and performance was analysed, particularly with regard to the false-alert rate. The results indicate that the new detection methods can provide timely warnings of imminent conflicts more consistently than Conflict Alert.

Paielli, Russell A.↗
NASA NTRS2005

Automated Wildfire Detection Through Artificial Neural Networks

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

Miller, Jerry↗
NASA NTRS2007

Applicability of a Conservative Margin Approach for Assessing NDE Flaw Detectability

Nondestructive Evaluation (NDE) procedures are required to detect flaws in structures with a high percentage detectability and high confidence. Conventional Probability of Detection (POD) methods are statistical in nature and require detection data from a relatively large number of flaw specimens. In many circumstances, due to the high cost and long lead time, it is impractical to build the large set of flaw specimens that is required by the conventional POD methodology. Therefore, in such situations it is desirable to have a flaw detectability estimation approach that allows for a reduced number of flaw specimens but provides a high degree of confidence in establishing the flaw detectability size. This paper presents an alternative approach called the conservative margin approach (CMA). To investigate the applicability of the CMA approach, flaw detectability sizes determined by the CMA and POD approaches have been compared on actual datasets. The results of these comparisons are presented and the applicability of the CMA approach is discussed.

Koshti, ajay M.↗
NASA NTRS2007

An Automated Flying-Insect Detection System

An automated flying-insect detection system (AFIDS) was developed as a proof-of-concept instrument for real-time detection and identification of flying insects. This type of system has use in public health and homeland-security decision support, agriculture and military pest management, and/or entomological research. Insects are first lured into the AFIDS integrated sphere by insect attractants. Once inside the sphere, the insect s wing beats cause alterations in light intensity that is detected by a photoelectric sensor. Following detection, the insects are encouraged (with the use of a small fan) to move out of the sphere and into a designated insect trap where they are held for taxonomic identification or serological testing. The acquired electronic wing-beat signatures are preprocessed (Fourier transformed) in real time to display a periodic signal. These signals are sent to the end user where they are graphically. All AFIDS data are preprocessed in the field with the use of a laptop computer equipped with LabVIEW. The AFIDS software can be programmed to run continuously or at specific time intervals when insects are prevalent. A special DC-restored transimpedance amplifier reduces the contributions of low-frequency background light signals, and affords approximately two orders of magnitude greater AC gain than conventional amplifiers. This greatly increases the signal-to-noise ratio and enables the detection of small changes in light intensity. The AFIDS light source consists of high-intensity Al-GaInP light-emitting diodes (LEDs). The AFIDS circuitry minimizes brightness fluctuations in the LEDs and when integrated with an integrating sphere, creates a diffuse uniform light field. The insect wing beats isotropically scatter the diffuse light in the sphere and create wing-beat signatures that are detected by the sensor. This configuration minimizes variations in signal associated with insect flight orientation. Preliminary data indicate that AFIDS has sufficient sensitivity and frequency measuring capability to differentiate between male and female mosquitoes (Figure 1, bottom panel) and fruit flies (data not shown). Similar studies show that AFIDS can be utilized to detect discrete differences between two mosquito species, Aedes aegypti and Aedes albopictus. When fully deployable, a wireless network of AFIDS monitors could be used in combination with other remotely sensed data and visually displayed in a geographic information system (GIS) to provide real-time surveillance (see Figure 2). More accurate and sensitive insect population forecasts and effective rapid response and mitigation of insect issues would then be possible.

Vann, Timi↗