Sensor Front-end Research Articles

A low-power consumption security data fusion model for Industrial Internet of Things

Industrial Internet of Things (IIOT) is an important part of manufacturing industry in the future, and the front-end sensor data acquisition network is the core component of it. Due to the limited energy of IIOT, reducing transmission interaction, energy consumption, and computational complexity in the process of data transmission is the key and difficult point in designing model of IIOT. In this paper, a lightweight green security data fusion model for IIOT is proposed, called LCSDF model, which aims to achieve data security and integrity verifiability by using less energy consumption. The simulation results show that the proposed model can ensure data security and verifiability, and meet the energy consumption requirements of the system. The performance of the algorithm is also satisfactory, reflecting the lightweight, green, and security of the model.

A 0.037 pJ K2$\text{K}^2$ 338 pW temperature sensor based on dynamic leakage‐suppression logic

AbstractThis letter introduces an ultra‐low‐power temperature sensor utilizing dynamic leakage‐suppression (DLS) logic and thoroughly analyses its working principle. The sensor effectively tackles the weak pull‐up challenge inherent in DLS logic ensuring its compatibility with standard digital logic. By capitalizing on the super cut‐off attribute of DLS logic, the frontend of the sensor achieves ultra‐low power consumption, without compromising on measurement precision or the breadth of the temperature range. The digital part of the proposed utilizes the output frequency of the sensor's frontend as the clock source, in conjunction with an external 50 Hz reference clock, achieving a low overall power consumption. The frontend of the temperature sensor was fabricated using a 180 nm process, occupying a minimal area of 374 . The digital part of the circuit is implemented using FPGA. Following a two‐point calibration and system error removal, the sensor, operating at a supply voltage of 0.8 V, demonstrated a error of across the temperature range of −20 to 125 . At 25 , the resolution figure of merit of the sensor was 0.037 pJ , with a maximum voltage sensitivity of 4.2 .

Ultra-low noise front-end design for smart optical sensors with high sensitivity and wide dynamic range.

Ultra-low noise is a critical component in the design of high-precision sensor front-ends. We introduced differential phase-sensitive detection (d-PSD) to mitigate both multiplicative and additive noise in optical sensors, aiming for an enhanced performance and cost-effectiveness. The d-PSD combines a capacitive transimpedance amplifier (C-TIA), a delta-sigma analog-to-digital converter (ΔΣ-ADC), and a software-based lock-in amplifier (s-LIA). The first two components utilize the DDC112 (a dual current input 20-bit ADC) for a minimal analog channel length, thus reducing noise efficiently, while the latter employs a cost-effective 32-bit microcontroller unit (MCU), the HC32F460. This approach was successfully implemented as the front-end for a smart optical sensor. Testing indicated that the sensor achieved an equivalent current noise level of 0.6 nA/√Hz, primarily attributed to the light source driver rather than the sensor's front-end circuit. The sensor exhibited an exceptional performance, with a 3σ measurement precision of 5.4 × 10-4 over a 1-second integration time and a dynamic range of 100 dB, leveraging the proposed method and design. Furthermore, the front-end of the sensor boasts a compact size, low power consumption, and affordability, making it an ideal, versatile solution for ultra-high precision, smart optical sensors.

Sensitivity improvement in the measurement of minor components by spatial confinement in fiber-optic laser-induced breakdown spectroscopy

Nuclear power overhaul can benefit from a fiber-optic laser-induced breakdown spectroscopy (FO-LIBS) setup for in situ composition measurements. Regarding FO-LIBS, the pulsed energy of the fiber-delivery laser is limited, and the spot profile received by the sample surface is distorted from a Gaussian to a flat-top distribution. Therefore, the induced plasma in FO-LIBS is characterized by weakened emission, shortened lifetime, and insufficient sampling of minor components compared with that of conventional LIBS. This could not meet the quantitative demands of the minor component with a concentration of 0.01 wt% or lower in structural steel. In this study, by modifying the mechanical structure of the front-end sensor, a space constraint condition can be created for plasma emission enhancement. By combining the optical diagnostics of fast photograph and shadowgraph, shockwave propagation and plasma expansion can be visualized synchronously. The reflected shockwave decelerates in the process of propagating towards the plasma, accompanied by morphological changes from the oblate cylinder to the hemisphere. It can be demonstrated that the plasma is constricted by the reflected shockwave associated with a significant increase in the plasma temperature and electron number density. The plate spacing determines the time delay of spectral enhancement and also determines the enhancement factor corresponding to the velocity attenuation of shockwave propagation over a long distance. The enhancement factor is found to be inversely proportional to the quadratic square of the propagation velocity of shockwave just after reflection, and shows an upward trend with increasing upper-level energy of atomic transitions. A maximum enhancement factor of ∼3.52 is realized with a time delay of 4 μs at a plate spacing of 3 mm, and trace components Mo, V, and Cu are newly recognized, which cannot be observed in conventional FO-LIBS. Meanwhile, the calibration of trace Cr and Mn suggests that the quantitative results using the sensor coupled with spatial confinement are comparable, and the limits of detection are reduced to 31 ppm and 475 ppm, respectively.

An Energy-Efficient Small-Area Configurable Analog Front-End Interface for Diverse Biosignals Recording.

We introduce a fully integrated configurable analog front-end (CAFE) sensor intended to accommodate various types of bio-potential signals in this article. The proposed CAFE is composed of an AC-coupled chopper-stabilized amplifier to effectively reduce 1/f noise and an energy- and area-efficient tunable filter to tune this interface to the bandwidth of various specific signals of interest. A tunable active-pseudo-resistor is integrated into the amplifier's feedback to realize a reconfigurable high-pass cutoff frequency and enhance its linearity, while the filter is designed using a subthreshold-source-follower-based pseudo-RC (SSF-PRC) topology to attain the required super-low cutoff frequency without the need for extremely low biasing current sources. Implemented in TSMC 40 nm technology, the chip occupies an active area of 0.048 [Formula: see text] while consuming 2.47 μW DC power from a 1.2-V supply voltage. Measurement results indicate that the proposed design achieved a mid-band gain of 37 dB, with an integrated input-referred noise ( VIRN) of 1.7 μVrms within 1-260 Hz. The total harmonic distortion (THD) of the CAFE is below 1 % with a 2.4 m Vpp input signal. With a wide-range bandwidth adjustment capability, the proposed CAFE can be used in both wearable and implantable recording devices to acquire different bio-potential signals.

Wireless, Multi-Sensor System-on-Chip for pH and Amperometry Powered by Body Heat.

This article presents a body-heat-powered, multi-sensor SoC for measurement of chemical and biological sensors. Our approach combines analog front-end sensor interfaces for voltage- (V-to-I) and current-mode (potentiostat) sensors with a relaxation oscillator (RxO) readout scheme targeting << 10 μW power consumption. The design was implemented as a complete sensor readout system-on-chip, including a low-voltage energy harvester compatible with thermoelectric generation and a near-field wireless transmitter. A prototype IC was fabricated in a 0.18 μm CMOS process as a proof-of-concept. As measured, full-range pH measurement consumes 2.2 μW at maximum, where the RxO consumes 0.7 μW and measured linearity of the readout circuit demonstrates R 2 0.999. Glucose measurement is also demonstrated using an on-chip potentiostat circuit as the input of the RxO, with a readout power consumption as low as 1.4 μ W. As a final proof-of-principle, both pH and glucose measurement are demonstrated while powering from body heat using a centimeter-scale thermoelectric generator on the skin surface, and pH measurement is further demonstrated with an on-chip transmitter for wireless data transmission. Long-term, the presented approach may enable a variety of biological, electrochemical, and physical sensor readout schemes with microwatt operation for batteryless and power autonomous sensor systems.

Memory Conscious Machine Learning Method to Extract Time-of-Flight Data From Flash LiDARs

This letter presents a memory-conscious architecture for single-photon-avalanche-diode (SPAD) light detection and ranging (LiDAR) systems to extract time-of-flight (ToF) information by learning the distribution of incoming photons' ToF to reduce the I/O bandwidth required by flash LiDAR digitizers. Such LiDAR systems can be sensitive to single photons, which makes them an excellent choice for both short- and long-range applications. However, counting and processing every photon means that the sensor front-end generates a massive amount of data to be processed in each frame. The proposed architecture will tackle this challenge by learning the incoming photons' distribution on-chip using mini-batches of time-stamped data from time-to-digital converters. Hence, only learned parameters need to be transferred off-chip instead of the raw data to re-create the histogram. We demonstrate the feasibility of this model in a Monte Carlo simulation.

An artificial neural network-based data filling approach for smart operation of digital wastewater treatment plants

With the prevalence of digitization, smart operation has become mainstream in future wastewater treatment plants. This requires substantial and complete historical data for model construction. However, the data collected from the front-end sensor contained numerous missing dissolved oxygen (DO) values. Therefore, this study proposed a framework that adaptively adjusted the structure of embedded filling models according to the missing situation. Long short-term memory and gated recurrent units (GRU) were embedded for experiments, and some standard filling methods were selected as benchmarks. The experimental dataset indicated that the K-nearest neighbor could achieve good filling results by traversing the parameters. The effect obtained by the method proposed in this study was slightly better, and GRU was better among the three embedded models. Analysis of the filling results for each DO column revealed that the effect was highly correlated with the dispersion of DO data. The experimental results for the entire dataset demonstrated that the filling effect of the proposed method was significantly better and more stable than the others. The proposed model suffered from the problem of insufficient interpretability and long training time. This study provides an efficient and practical method to solve the intricate missing DO and lays the foundation for the smart operation of wastewater treatment plants.

Smart Glove With Fully Integrated Textile Sensors and Wireless Sensor Frontend for the Tactile Internet

In this letter, we present a smart glove for Tactile Internet applications. The individual finger motions are measured via resistive strain sensors. The strain sensors are directly integrated with the textile glove and are produced in an automated process. The sensor glove is integrated with sensor conditioning, controller, wireless frontend, and battery. We investigate the measured sensor data for a variety of gestures, demonstrating the good quality of the data allowing for easy and low-energy gesture recognition.

Real-Time Human Motion Tracking by Tello EDU Drone

Human movement tracking is useful in a variety of areas, such as search-and-rescue activities. CCTV and IP cameras are popular as front-end sensors for tracking human motion; however, they are stationary and have limited applicability in hard-to-reach places, such as those where disasters have occurred. Using a drone to discover a person is challenging and requires an innovative approach. In this paper, we aim to present the design and implementation of a human motion tracking method using a Tello EDU drone. The design methodology is carried out in four steps: (1) control panel design; (2) human motion tracking algorithm; (3) notification systems; and (4) communication and distance extension. Intensive experimental results show that the drone implemented by the proposed algorithm performs well in tracking a human at a distance of 2-10 m moving at a speed of 2 m/s. In an experimental field of the size 95×35m2, the drone tracked human motion throughout a whole day, with the best tracking results observed in the morning. The drone was controlled from a laptop using a Wi-Fi router with a maximum horizontal tracking distance of 84.30 m and maximum vertical distance of 13.40 m. The experiment showed an accuracy rate for human movement detection between 96.67 and 100%.

Batteryless, Wireless, and Secure SoC for Implantable Strain Sensing

The past few years have witnessed a growing interest in wireless and batteryless implants, due to their potential in long-term biomedical monitoring of in-body conditions such as internal organ movements, bladder pressure, and gastrointestinal health. Early proposals for batteryless implants relied on inductive near-field coupling and ultrasound harvesting, which require direct contact between the external power source and the human body. To overcome this near-field challenge, recent research has investigated the use of RF backscatter in wireless micro-implants because of its ability to communicate with wireless receivers that are placed at a distance outside the body ( 0.5 m), allowing a more seamless user experience. Unfortunately, existing far-field backscatter designs remain limited in their functionality: they cannot perform biometric sensing or secure data transmission; they also suffer from degraded harvesting efficiency and backscatter range due to the impact of variations in the surrounding tissues. In this paper, we present the design of a batteryless, wireless and secure system-on-chip (SoC) implant for in-body strain sensing. The SoC relies on four features: 1) employing a reconfigurable in-body rectenna which can operate across tissues adapting its backscatter bandwidth and center frequency; 2) designing an energy efficient 1.37 mmHg strain sensing front-end with an efficiency of 5.9 mmHg·nJ/conversion; 3) incorporating an AES-GCM security engine to ensure the authenticity and confidentiality of sensed data while sharing the ADC with the sensor interface for an area efficient random number generation; 4) implementing an over-the-air closed-loop wireless programming scheme to reprogram the RF front-end to adapt for surrounding tissues and the sensor front-end to achieve faster settling times below 2 s.

Time reversal mirror for hyperthermia ofmulti-focal breast tumors using electromagnetic time reversal technique

ABSTRACT Motivated by the quest to curtail the high mortality rate of breast cancer, the manuscript proposes the sensitivity enhancement of monopole antenna for hyperthermia application by using electromagnetic time reversal (EMTR) technique with transformation structures for early treatment of multi-focal breast tumors. The EMTR technique is characterized with temporal and spatial focusing, hence enhancing the visibility of tumors embedded in the breast medium. In this study, we aim at the non-invasive power deposition on sub-wavelength-sized tumors at sub-wavelength separation incorporation with sub-wavelength scatterers. The paper is focused on enhancing the sensitivity of scattering reception in TR algorithm for hyperthermia application using sub-wavelength sized scatterers. The proposed applicator is an ultra-wideband (UWB) monopole antenna designed with sub-wavelength-sized split ring embedded square patch (SRESP) on a grounded substrate placed below it at some distance to serve as near field scatterer. Another plate of sub-wavelength scatterers but without the ground plate is placed in close proximity to the unhealthy breast in-conjunction with four ultra-wideband antenna time reversal mirrors (UWB-TRM). The proposed method shows promising potential for the selective power deposition for hyperthermia of sub-wavelength-sized tumors at sub-wavelength separations. This technique of enhancing front-end sensor sensitivity can also be extended to other optimization techniques for selective power deposition in hyperthermia of breast cancer.

A 10 M Ω, 50 kHz-40 MHz Impedance Measurement Architecture for Source-Differential Flow Cytometry.

A low-power, impedance-based integrated circuit (IC) readout architecture is presented for cell analysis and cytometry applications. A three-electrode layout and source-differential excitation cancels baseline current prior to the sensor front-end, which enables the use of a high-gain readout circuit for the difference current. A lock-in architecture is employed with down-conversion and up-conversion in the feedback loop, enabling high closed-loop gain (up to 10 M Ω) and high bandwidth (up to 40 MHz). A hybrid-RC feedback network mitigates the SNR degradation seen over a wide operating frequency range when using purely capacitive feedback. The effect of phase shift on the closed-loop system gain and noise performance are analyzed in detail, along with optimization strategies, and the design includes fine-grained phase adjustment to minimize phase error. The impedance sensor was fabricated in a 0.18 μ m CMOS process and consumes 9.7 mW with an operating frequency from 50 kHz to 40 MHz and provides adjustable bandwidth. Measurements demonstrate that the impedance sensor achieves 6 pA [Formula: see text] input-referred noise over 200 Hz bandwidth at 0.5 MHz modulation frequency. Combined with a microfluidic flow cell, measured results using this source-differential measurement approach are presented using both monodisperse and polydisperse sample solutions and demonstrate single-cell resolution, detecting 3 μ m diameter particles in solution with 22 dB SNR.

Energy Efficient Pixel-Parallel Read-Out Circuits for Digital Image Sensors Using Cross-Layer Pixel Depth Control

Digital pixel sensors with pixel-parallel readout provide opportunities for high frame rate and high resolution in 3D integrated camera platforms with in-sensor machine learning. The active energy consumption of the digital pixels at the sensor front end is a key performance parameter for applications involving smart cameras. This work proposes a novel digital pixel design that utilizes cross-layer feedback to improve active energy efficiency of pixels in image sensors. An algorithm-circuit co-simulation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$336\times256$ </tex-math></inline-formula> image sensor in 65nm CMOS for an object detection task shows 58% active energy saving in digital pixel circuits, while maintaining accuracy of end task.

Low-Loss Heterogeneous Integrations With High Output Power Radar Applications at W-Band

This study presents a design of a 94-GHz high-performance and highly compact frequency-modulated continuous-wave radar sensor. In this sensor, an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> -band CMOS-based all-digital phase-locked loop chip, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$W$ </tex-math></inline-formula> -band SiGe-based transceiver monolithic microwave integrated circuit (MMIC), and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$W$ </tex-math></inline-formula> -band GaN-based MMIC power amplifier (PA) are heterogeneously integrated (HI). Each part of the 130-nm bipolar complementary metal-oxide-semiconductor (BiCMOS) SiGe-based transceiver MMIC is designed to include a low-noise amplifier, PA, octupler, mixer, and lange coupler. The fabrication process of our in-house silicon-based MEMS photosensitive composite film is developed to provide very high-density integration and very low insertion loss of interconnections between chips. The HI front end of the radar sensor is measured on-wafer with a high output power of 22 dBm. Moreover, a low double-sideband noise figure (NF) of 10.2 dB is obtained. Bonding–substrate integrated waveguide (SIW)–WG transitions between the heterogeneously integrated front end and the antenna are specially designed and verified. A 2.3-dB degradation is observed, where 19.7 dBm is measured at the transmitter WG WR-10-flange. Thus, the sensor offers a 55-dB dynamic range at a 2-m position with an expectation of a long-distance target-detection range. The radar sensor has an 11.7-cm range resolution and is only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$60\times 40\times $ </tex-math></inline-formula> 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> in size, with a weight of only 78 g.

DYNAMIC NONLINEAR CORRECTION PROCESSING OF PRESSURE SENSOR TEST SIGNAL IN INTERNET OF THINGS SYSTEM

In order to further explore the intelligent research of the pressure sensor in the pipeline, based on the existing pipeline detection methods of the Internet of Things (IoT), the signal processing method and correction research in the wireless sensor network of the IoT are explored. A multi-pressure sensor detection method of negative pressure wave is proposed. Scientific and intelligent means are used to explore the pipeline remote intelligent detection. The specific research results are as follows. In the simulation study, when the working condition of pump station 1# changes, the pressure wave first reaches A1 and B2 sensors, and finally reaches C1 and C2 sensors. If there is leakage in the pipeline, the simulation results show that when the pressure of pump station rises to 5[Formula: see text]MPa, the pressure of B1 and B2 test points decreases to about 4.9[Formula: see text]MPa, and the pressure of A1, A2, C1 and C2 test points is about 3[Formula: see text]MPa; when the pressure of the pump station drops to 3[Formula: see text]MPa, the pressure of all test points decreases. Generally speaking, the pressure of the front-end pressure sensor of the pump station is basically unchanged while the pressure of the back end increases when the pressure increases; when the pressure decreases, the pressure of the front-end pressure sensor of the pump station is basically unchanged while the pressure of all the back-end pressure sensor decreases. After correction, the signal data is obviously smooth and the error is obviously reduced. This study can provide scientific and effective reference for the pressure monitoring of IoT sensor network.

A Supply-Voltage Driving Scheme for Grounded Capacitive Sensor Front-Ends

In this article, a novel supply-voltage driving scheme for capacitive sensor front-ends is proposed to eliminate the parasitic capacitances effects. The suggested circuit is intended for remote sensors (and, hence, connected to the circuit through a shielded cable) with one electrode grounded and of low capacitance (in the 0-10 pF range). The effects of the parasitic capacitance of the cable are avoided using the active-shielding technique, whereas those of the amplifier input through a smart driving of the reference node of the amplifier supply voltage. Thanks to these techniques, the input-output characteristic shows, without applying any adjustment and/or calibration, an offset error lower than 3 fF. The non-linearity error is in the order of 0.01% of the full-scale span, which corresponds to 1 fF. Different operational amplifiers and different lengths (up to 15 meters) of the interconnecting cable are experimentally tested to demonstrate the feasibility of the circuit. In comparison with similar circuits recently suggested in the literature, the proposed circuit does not require any bulky component, such as a transformer, and consequently it is a lower cost solution and suitable to be integrated.

A High Temperature SOI-CMOS Chipset Focusing Sensor Electronics for Operating Temperatures up to 300°C

Abstract Sensors are the key elements for capturing environmental properties and are increasingly important in the industry for the intelligent control of industrial processes. While in many everyday objects highly integrated sensor systems are already state of the art, the situation in an industrial environment is clearly different. Frequently, the use of sensor systems is impossible, because the extreme ambient conditions of industrial processes like high operating temperatures or strong mechanical load do not allow the reliable operation of sensitive electronic components. Fraunhofer is running the Lighthouse Project “eHarsh” to overcome this hurdle. In the course of the project, an integrated sensor readout electronic has been realized based on a set of three chips. A dedicated sensor fron-tend provides the analog sensor interface for resistive sensors typically arranged in a Wheatstone configuration. Furthermore, the chipset includes a 32-bit microcontroller for signal conditioning and sensor control. Finally, it comprises an interface chip including a bus transceiver and voltage regulators. The chipset has been realized in a high-temperature 0.35-micron SOI-CMOS technology focusing operating temperatures up to 300°C. The chipset is assembled on a multilayer ceramic low-temperature cofired ceramics (LTCC) board using flip chip technology. The ceramic board consists of four layers with a total thickness of approximately 0.9 mm. The internal wiring is based on silver paste while the external contacts were alternatively manufactured in silver (sintering/soldering) or in gold alloys (wire bonding). As an interconnection technology, silver sintering has been applied. It has already been shown that a significant increase in lifetime can be reached by using silver sintering for die attach applications. Using silver sintering for flip chip technology is a new and challenging approach. By adjusting the process parameter geared to the chipset design and the design of the ceramic board high-quality flip chip interconnects can be generated.

Intelligent Electromagnetic Sensors for Non-Invasive Trojan Detection.

Rapid growth of sensors and the Internet of Things is transforming society, the economy and the quality of life. Many devices at the extreme edge collect and transmit sensitive information wirelessly for remote computing. The device behavior can be monitored through side-channel emissions, including power consumption and electromagnetic (EM) emissions. This study presents a holistic self-testing approach incorporating nanoscale EM sensing devices and an energy-efficient learning module to detect security threats and malicious attacks directly at the front-end sensors. The built-in threat detection approach using the intelligent EM sensors distributed on the power lines is developed to detect abnormal data activities without degrading the performance while achieving good energy efficiency. The minimal usage of energy and space can allow the energy-constrained wireless devices to have an on-chip detection system to predict malicious attacks rapidly in the front line.

A Fully Integrated Low-Power Capacitive Sensor Frontend With Automatic Tuning Scheme

A Fully Integrated Low-Power Capacitive Sensor Frontend With Automatic Tuning Scheme