Smart industrial IoT monitoring and control system based on UAV and cloud computing applied to a concrete plant

Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besides quantifying production and helping to make decisions. UAVs are a highly consistent technological platform for efficient and cost-effective data collection and event monitoring. The industrial Internet of things (IIoT) sends data from systems that monitor and control the physical world to data processing systems that cloud computing has shown to be important tools for meeting processing requirements. In fog computing, the IoT gateway links different objects to the internet. It can operate as a joint interface for different networks and support different communication protocols. A great deal of effort has been put into developing UAVs and multi-UAV systems. This paper introduces a smart IIoT monitoring and control system based on an unmanned aerial vehicle that uses cloud computing services and exploits fog computing as the bridge between IIoT layers. Its novelty lies in the fact that the UAV is automatically integrated into an industrial control system through an IoT gateway platform, while UAV photos are systematically and instantly computed and analyzed in the cloud. Visual supervision of the plant by drones and cloud services is integrated in real-time into the control loop of the industrial control system. As a proof of concept, the platform was used in a case study in an industrial concrete plant. The results obtained clearly illustrate the feasibility of the proposed platform in providing a reliable and efficient system for UAV remote control to improve product quality and reduce waste. For this, we studied the communication latency between the different IIoT layers in different IoT gateways.The authors would like to thank the Seneca Foundation as also FRUMECAR S.L., for their support and the opportunity to implement and test the proposed approach on their facilities. This work was partially supported by FRUMECAR S.L. and Seneca Foundation's "Murcia Regional Scientific Excellence Research Program" (Murcia Science and Technology Agency-19895/GERM/15)

A Millimeter-Wave Coexistent RFIC Receiver Architecture in 0.18-µm SiGe BiCMOS for Radar and Communication Systems

Innovative circuit architectures and techniques to enhance the performance of several key BiCMOS RFIC building blocks applied in radar and wireless communication systems operating at the millimeter-wave frequencies are addressed in this dissertation. The former encapsulates the development of an advanced, low-cost and miniature millimeter-wave coexistent current mode direct conversion receiver for short-range, high-resolution radar and high data rate communication systems. A new class of broadband low power consumption active balun-LNA consisting of two common emitters amplifiers mutually coupled thru an AC stacked transformer for power saving and gain boosting. The active balun-LNA exhibits new high linearity technique using a constant gm cell transconductance independent of input-outputs variations based on equal emitters’ area ratios. A novel multi-stages active balun-LNA with innovative technique to mitigate amplitude and phase imbalances is proposed. The new multi-stages balun-LNA technique consists of distributed feed-forward averaging recycles correction for amplitude and phase errors and is insensitive to unequal paths parasitic from input to outputs. The distributed averaging recycles correction technique resolves the amplitude and phase errors residuals in a multi-iterative process. The new multi-stages balun-LNA averaging correction technique is frequency independent and can perform amplitude and phase calibrations without relying on passive lumped elements for compensation. The multi-stage balun-LNA exhibits excellent performance from 10 to 50 GHz with amplitude and phase mismatches less than 0.7 dB and 2.86º, respectively. Furthermore, the new multi-stages balun-LNA operates in current mode and shows high linearity with low power consumption. The unique balun-LNA design can operates well into mm-wave regions and is an integral block of the mm-wave radar and communication systems. The integration of several RFIC blocks constitutes the broadband millimeter-wave coexistent current mode direct conversion receiver architecture operating from 22- 44 GHz. The system and architectural level analysis provide a unique understanding into the receiver characteristics and design trade-offs. The RF front-end is based on the broadband multi-stages active balun-LNA coupled into a fully balanced passive mixer with an all-pass in-phase/quadrature phase generator. The trans-impedance amplifier converts the input signal current into a voltage gain at the outputs. Simultaneously, the high power input signal current is channelized into an anti-aliasing filter with 20 dB rejection for out of band interferers. In addition, the dissertation demonstrates a wide dynamic range system with small die area, cost effective and very low power consumption

A Millimeter-Wave Coexistent RFIC Receiver Architecture in 0.18-µm SiGe BiCMOS for Radar and Communication Systems

Innovative circuit architectures and techniques to enhance the performance of several key BiCMOS RFIC building blocks applied in radar and wireless communication systems operating at the millimeter-wave frequencies are addressed in this dissertation. The former encapsulates the development of an advanced, low-cost and miniature millimeter-wave coexistent current mode direct conversion receiver for short-range, high-resolution radar and high data rate communication systems. A new class of broadband low power consumption active balun-LNA consisting of two common emitters amplifiers mutually coupled thru an AC stacked transformer for power saving and gain boosting. The active balun-LNA exhibits new high linearity technique using a constant gm cell transconductance independent of input-outputs variations based on equal emitters’ area ratios. A novel multi-stages active balun-LNA with innovative technique to mitigate amplitude and phase imbalances is proposed. The new multi-stages balun-LNA technique consists of distributed feed-forward averaging recycles correction for amplitude and phase errors and is insensitive to unequal paths parasitic from input to outputs. The distributed averaging recycles correction technique resolves the amplitude and phase errors residuals in a multi-iterative process. The new multi-stages balun-LNA averaging correction technique is frequency independent and can perform amplitude and phase calibrations without relying on passive lumped elements for compensation. The multi-stage balun-LNA exhibits excellent performance from 10 to 50 GHz with amplitude and phase mismatches less than 0.7 dB and 2.86º, respectively. Furthermore, the new multi-stages balun-LNA operates in current mode and shows high linearity with low power consumption. The unique balun-LNA design can operates well into mm-wave regions and is an integral block of the mm-wave radar and communication systems. The integration of several RFIC blocks constitutes the broadband millimeter-wave coexistent current mode direct conversion receiver architecture operating from 22- 44 GHz. The system and architectural level analysis provide a unique understanding into the receiver characteristics and design trade-offs. The RF front-end is based on the broadband multi-stages active balun-LNA coupled into a fully balanced passive mixer with an all-pass in-phase/quadrature phase generator. The trans-impedance amplifier converts the input signal current into a voltage gain at the outputs. Simultaneously, the high power input signal current is channelized into an anti-aliasing filter with 20 dB rejection for out of band interferers. In addition, the dissertation demonstrates a wide dynamic range system with small die area, cost effective and very low power consumption

Time domain based image generation for synthetic aperture radar on field programmable gate arrays

Aerial images are important in different scenarios including surface cartography, surveillance, disaster control, height map generation, etc. Synthetic Aperture Radar (SAR) is one way to generate these images even through clouds and in the absence of daylight. For a wide and easy usage of this technology, SAR systems should be small, mounted to Unmanned Aerial Vehicles (UAVs) and process images in real-time. Since UAVs are small and lightweight, more robust (but also more complex) time-domain algorithms are required for good image quality in case of heavy turbulence. Typically the SAR data set size does not allow for ground transmission and processing, while the UAV size does not allow for huge systems and high power consumption to process the data. A small and energy-efficient signal processing system is therefore required. To fill the gap between existing systems that are capable of either high-speed processing or low power consumption, the focus of this thesis is the analysis, design, and implementation of such a system. A survey shows that most architectures either have to high power budgets or too few processing capabilities to match real-time requirements for time-domain-based processing. Therefore, a Field Programmable Gate Array (FPGA) based system is designed, as it allows for high performance and low-power consumption. The Global Backprojection (GBP) is implemented, as it is the standard time-domain-based algorithm which allows for highest image quality at arbitrary trajectories at the complexity of O(N3). To satisfy real-time requirements under all circumstances, the accelerated Fast Factorized Backprojection (FFBP) algorithm with a complexity of O(N2logN) is implemented as well, to allow for a trade-off between image quality and processing time. Additionally, algorithm and design are enhanced to correct the failing assumptions for Frequency Modulated Continuous Wave (FMCW) Radio Detection And Ranging (Radar) data at high velocities. Such sensors offer high-resolution data at considerably low transmit power which is especially interesting for UAVs. A full analysis of all algorithms is carried out, to design a highly utilized architecture for maximum throughput. The process covers the analysis of mathematical steps and approximations for hardware speedup, the analysis of code dependencies for instruction parallelism and the analysis of streaming capabilities, including memory access and caching strategies, as well as parallelization considerations and pipeline analysis. Each architecture is described in all details with its surrounding control structure. As proof of concepts, the architectures are mapped on a Virtex 6 FPGA and results on resource utilization, runtime and image quality are presented and discussed. A special framework allows to scale and port the design to other FPGAs easily and to enable for maximum resource utilization and speedup. The result is streaming architectures that are capable of massive parallelization with a minimum in system stalls. It is shown that real-time processing on FPGAs with strict power budgets in time-domain is possible with the GBP (mid-sized images) and the FFBP (any image size with a trade-off in quality), allowing for a UAV scenario

Using global existing fiber networks for environmental sensing

We review recent advances in distributed fiber optic sensing (DFOS) and their applications. The scattering mechanisms in glass, which are exploited for reflectometry-based DFOS, are Rayleigh, Brillouin, and Raman scatterings. These are sensitive to either strain and/or temperature, allowing optical fiber cables to monitor their ambient environment in addition to their conventional role as a medium for telecommunications. Recently, DFOS leveraged technologies developed for telecommunications, such as coherent detection, digital signal processing, coding, and spatial/frequency diversity, to achieve improved performance in terms of measurand resolution, reach, spatial resolution, and bandwidth. We review the theory and architecture of commonly used DFOS methods. We provide recent experimental and field trial results where DFOS was used in wide-ranging applications, such as geohazard monitoring, seismic monitoring, traffic monitoring, and infrastructure health monitoring. Events of interest often have unique signatures either in the spatial, temporal, frequency, or wavenumber domains. Based on the temperature and strain raw data obtained from DFOS, downstream postprocessing allows the detection, classification, and localization of events. Combining DFOS with machine learning methods, it is possible to realize complete sensor systems that are compact, low cost, and can operate in harsh environments and difficult-to-access locations, facilitating increased public safety and smarter cities

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Real-time processing of physiological signals for feedback control

Extensive studies about neural mechanisms involved in insect flight control have been carried out. Adaptive control of locomotion requires integration of salient sensory cues with ongoing motor activity. During flight, inputs received by an organism through sensory organs are processed by the central nervous system (CNS) and the integrated output thus obtained plays a significant role in controlling the wing phase shifts and flight muscle depressor asymmetries associated with adaptive flight maneuvers. The resulting maneuvers, in turn, bring a change in the insect’s sensory environment, thereby closing the feedback loop. Research on insect flight has been carried out using immobile preparations (tethered) and mobile preparations (free flight – untethered). There are pros and cons associated with the tethered and the untethered approach. The tethered approach, however, provides an easier way to study the CNS and its role in motor control of flight. Insects such as locusts and moths exhibit pertinent wing phase shifts and asymmetries in depressor muscles. For locusts constant wing phase shifts and m97 (forewing first basalar depressor muscle) depressor asymmetries have been observed during adaptive flight maneuvers making this a useful system for creation of behaviorally appropriate visual feedback. A method that utilizes asymmetrical timing of bilateral depressor muscles, the forewing first basalars (m97), of the locust to close a visual feedback loop in a computer-generated flight simulator is presented here. The method converts the time difference between left and right m97s to analog voltage values. Analog voltage values can be acquired using an open-loop experimental protocol (visual motion controlled by the experimenter), or can be used to control closed-loop experiments (muscle activity controls the visual stimuli) experiments. We recorded electromyographic (EMG) activity from right and left m97 muscles. On testing this circuit with real animals, we were able to detect the spike time difference and convert it to voltage values. These voltage values were utilized to control the presentation of a stimulus in a closed-loop environment. The feedback circuit presented here may be used in conjunction with the flight simulator(s) to understand the neural mechanisms involved in control of insect flight and provide further understanding of general mechanisms of neural control of behaviour

NASA Tech Briefs, December 2009

Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design

Evaluation of digital image compression algorithms for use on lap top computers

A technique for the evaluation of image compression algorithms was developed. This technique was then applied in the evaluation of six image compression algorithms (ARIDPCM, ISO/JPEG DCT, zonal DCT, proprietary wavelet, proprietary sub-band coding and the proprietary DCT). Of the six algorithms evaluated, the Wavelet algorithm performed the best on average in image quality at all bit rates. The JPEG DCT was concluded to be the most useful algorithm because of its performance and the advantages that come with being an international standard

DragonflEYE: a passive approach to aerial collision sensing

"This dissertation describes the design, development and test of a passive wide-field optical aircraft collision sensing instrument titled 'DragonflEYE'. Such a ""sense-and-avoid"" instrument is desired for autonomous unmanned aerial systems operating in civilian airspace. The instrument was configured as a network of smart camera nodes and implemented using commercial, off-the-shelf components. An end-to-end imaging train model was developed and important figures of merit were derived. Transfer functions arising from intermediate mediums were discussed and their impact assessed. Multiple prototypes were developed. The expected performance of the instrument was iteratively evaluated on the prototypes, beginning with modeling activities followed by laboratory tests, ground tests and flight tests. A prototype was mounted on a Bell 205 helicopter for flight tests, with a Bell 206 helicopter acting as the target. Raw imagery was recorded alongside ancillary aircraft data, and stored for the offline assessment of performance. The ""range at first detection"" (R0), is presented as a robust measure of sensor performance, based on a suitably defined signal-to-noise ratio. The analysis treats target radiance fluctuations, ground clutter, atmospheric effects, platform motion and random noise elements. Under the measurement conditions, R0 exceeded flight crew acquisition ranges. Secondary figures of merit are also discussed, including time to impact, target size and growth, and the impact of resolution on detection range. The hardware was structured to facilitate a real-time hierarchical image-processing pipeline, with selected image processing techniques introduced. In particular, the height of an observed event above the horizon compensates for angular motion of the helicopter platform.