Radiofrequency sensing systems based on emerging two-dimensional materials and devices

As one of the most promising platforms for wireless communication,radiofrequency(RF)electronics have been widely advocated for the development of sensing systems.In particular,monolayer and few-layer two-dimensional(2D)materials exhibiting extraordinary electrical properties not only can be integrated to improve the performance of RF circuits,but also to display exceptional sensing capabilities.This review provides an in-depth perspective of current trends and challenges in the application of 2D materials for RF biochemical sensing,including:(i)theoretical bases to achieve different sensing schemes;(ii)unique properties of 2D materials for reasoning their applications in RF sensing;(iii)developments in 2D RF sensors to facilitate the practice of biochemical sensors with ever-demanding sensitivities,as well as their potential uses in meeting the requirements and challenges of biochemical sensors in the Internet-of-Things era.

Influences of Atmospheric Turbulence on Image Resolution of Airborne and Space-Borne Optical Remote Sensing System

A new way is proposed to evaluate the influence of atmospheric turbulence on image resolution of airborne and space-borne optical remote sensing system, which is called as arrival angle-method. Applying this method, some engineering examples are selected to analyze the turbulence influences on image resolution based on three different atmospheric turbulence models quantificationally, for the airborne remote sensing system, the resolution errors caused by the atmospheric turbulence are less than 1 cm, and for the space-borne remote sensing system, the errors are around 1 cm. The results are similar to that obtained by the previous Friedmethod. Compared with the Fried-method, the arrival angle-method is rather simple and can be easily used in engineering fields.

A New Inertial Sensing System for Dynamic Measurement of Parallel Machines

One way to solve the problem of measurement precision caused by deformity for thermal expansion, friction and load etc is to use an inertial sensor to measure a change in the length of the rod on a parallel machine. However, the characteristic of dynamic measurement in the inertial sensing system and the effects of the machine＇s working environment, bias error, misalignment and wide band random noise in inertial measurement data results in the in-accuracy of system measurement. Therefore, on the basis of the measurement system a new inertial sensing system is proposed; the drifting of error is restrained with a method of inertial error correction and the system＇s position and the velocity state variables are predicted by the data fusion. After measuring the whole 300mm movement in an experiment, the analyses of the experimental result showed that the application of the new inertial sensing system can improve the positional accuracy about 61% and the movement precision more than 20%. Measurement results also showed that the application of the new inertial sensing system for dynamic measurement was a feasible method to improve the machine＇s dynamic positioning precision. And with the further improvement of the low-cost solid-stateacceleramenter technology, the application of the machine can take a higher position and make the speed dynamic accuracy possible.

Fiber Laser Based Multiplexed Sensing System

A laser sensing system based on beat frequency demodulation is proposed. The sensor uses a single-longitudinal-mode distributed Bragg reflector （DBR） fiber laser as a sensing element. This laser sensor has great multiplexing capability due to its wide free spectral range. Wavelength-division-multiplex （WDM） and frequency-division-multiplex （FDM） techniques are studied. The sensing system has high sensitivity and multiplexing channels.

Technical foundation research on high resolution remote sensing system of China's coastal zone

China's coastal zone is a region with a highly developed economy that contrasts clearly with the slow paced regular investigation on its natural environment,which cannot keep pace with the requirement of economic development and modern management.Laying a theoretical foundation for the modern management of China's costal zone is aimed at. This research focuses on the following processing and analyzing technologies for coastal zone high-resolution remote sensing data: organization and management of large amounts of high-resolution remote sensing data, quick and precise spatial positioning system,algorithms for image fusion in feature level and coastal zone feature extraction. They will form a technical foundation of the system. And, if combined with other research results such as coastal zone remote sensing classification system and its mapping subsystem, an advanced technical frame for remote sensing investigation of coastal zone resource will be constructed.

An operational satellite remote sensing system for ocean fishery

Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from -3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.

A remote sensing system of vehicle emissions based on tunable diode laser technology

As being an effective real-time method of monitoring vehicle emissions on-road, a remote sensing system based on the tunable diode laser （TDL） technology was presented, and the key technologies were discussed. A field test in Guangzhou（Guangdong, China） was performed and was found that the factors, such as slope, instantaneous speed and acceleration, had significant influence on the detectable rate of the system. Based on the results, the proposal choice of testing site was presented.

Stimulated Brillouin scattering-induced phase noise in an interferometric fiber sensing system

Stimulated Brillouin scattering-induced phase noise is harmful to interferometric fiber sensing systems. The localized fluctuating model is used to study the intensity noise caused by the stimulated Brillouin scattering in a single-mode fiber. The phase noise structure is analyzed for an interferometric fiber sensing system, and an unbalanced Michelson interferometer with an optical path difference of 1 m, as well as the phase-generated carrier technique, is used to measure the phase noise. It is found that the phase noise is small when the input power is below the stimulated Brillouin scattering threshold, increases dramatically at first and then gradually becomes flat when the input power is above the threshold, which is similar to the variation in relative intensity noise. It can be inferred that the increase in phase noise is mainly due to the broadening of the laser linewidth caused by stimulated Brillouin scattering, which is verified through linewidth measurements in the absence and presence of the stimulated Brillouin scattering.

Information Method for Synthesis of Optimal Data Subsystems Designated for Positioning, Location and Remote Sensing Systems

The general classification of information systems of remote action, including such system as positioning systems, location systems and remote sensing systems is suggested. In view of formulated limitation conditions the common mathematical information model of data transfer subsystems of considered systems is suggested. The optimization of developed information model is carried out and the optimal operation regimes of these data transfer subsystems are

Enhancing Task Assignment in Crowdsensing Systems Based on Sensing Intervals and Location

The popularity of mobile devices with sensors is captivating the attention of researchers to modern techniques,such as the internet of things(IoT)and mobile crowdsensing(MCS).The core concept behind MCS is to use the power of mobile sensors to accomplish a difficult task collaboratively,with each mobile user completing much simpler micro-tasks.This paper discusses the task assignment problem in mobile crowdsensing,which is dependent on sensing time and path planning with the constraints of participant travel distance budgets and sensing time intervals.The goal is to minimize aggregate sensing time for mobile users,which reduces energy consumption to encourage more participants to engage in sensing activities and maximize total task quality.This paper introduces a two-phase task assignment framework called location time-based algorithm(LTBA).LTBA is a framework that enhances task assignment in MCS,whereas assigning tasks requires overlapping time intervals between tasks and mobile users’tasks and the location of tasks and mobile users’paths.The process of assigning the nearest task to the mobile user’s current path depends on the ant colony optimization algorithm(ACO)and Euclidean distance.LTBA combines two algorithms:(1)greedy online allocation algorithm and(2)bio-inspired traveldistance-balance-based algorithm(B-DBA).The greedy algorithm was sensing time interval-based and worked on reducing the overall sensing time of the mobile user.B-DBA was location-based and worked on maximizing total task quality.The results demonstrate that the average task quality is 0.8158,0.7093,and 0.7733 for LTBA,B-DBA,and greedy,respectively.The sensing time was reduced to 644,1782,and 685 time units for LTBA,B-DBA,and greedy,respectively.Combining the algorithms improves task assignment in MCS for both total task quality and sensing time.The results demonstrate that combining the two algorithms in LTBA is the best performance for total task quality and total sensing time,and the greedy algorithm follows it then B-DBA.

A Composite Catalytic Oxidation-fluorescence Sensing System for 2,4-dichlorophenol Analysis based on Fe(Ⅲ)PcTs-BuOOH-CdTe QDs

The active oxygen species in the catalytic oxidation system of Fe(Ⅲ)PcTs-t-BuOOH were identified,and the mechanism of the catalytic oxidation of phenolic substrates was proposed.Quinone imine molecules,the main products of catalytic oxidation reaction,can be adsorbed on the surface of CdTe QDs,resulting in their fluorescence quenching.A dual function of catalytic oxidation and fluorescence sensing was developed for the determination of dichlorophenol(DCP)based on the Fe(Ⅲ)PcTs-BuOOH-CdTe QDs system.The linear detection range of DCP was 1×10^(-6)-1.3×10^(-4) mol/L,and the detection limit 2.4×10^(-7) mol/L.This method was characterized by high selectivity,good repeatability and desirable stability,presenting promising potentials for analyzing DCP concentration in real water samples.

High-g Shocking Testing of the Martlet Wireless Sensing System

This article reports the latest development of a wireless sensing system,named Martlet,on high-g shock acceleration measurement.The Martlet sensing node design is based on a Texas Instruments Piccolo microcontroller,with clock frequency programmable up to 90 MHz.The high clock frequency of the microcontroller enables Martlet to support high-frequency data acquisition and high-speed onboard computation.In addition,the extensible design of the Martlet node conveniently allows incorporation of multiple sensor boards.In this study,a high-g accelerometer interface board is developed to allow Martlet to work with the selected microelectromechanical system(MEMS)high-g accelerometers.Besides low-pass and highpass filters,amplification gains are also implemented on the high-g accelerometer interface board.Laboratory impact experiments are conducted to validate the performance of the Martlet wireless sensing system with the high-g accelerometer board.The results of this study show that the performance of the wireless sensing system is comparable to the cabled system.

Multi-Dimensional Anonymization for Participatory Sensing Systems

Participatory sensing systems are designed to enable community people to collect, analyze, and share information for their mutual benefit in a cost-effective way. The apparently insensitive information transmitted in plaintext through the inexpensive infrastructure can be used by an eavesdrop-per to infer some sensitive information and threaten the privacy of the partic-ipating users. Participation of users cannot be ensured without assuring the privacy of the participants. Existing techniques add some uncertainty to the actual observation to achieve anonymity which, however, diminishes data quality/utility to an unacceptable extent. The subset-coding based anonymiza-tion technique, DGAS [LCN 16] provides the desired level of privacy. In this research, our objective is to overcome this limitation and design a scheme with broader applicability. We have developed a computationally efficient sub-set-coding scheme and also present a multi-dimensional anonymization tech-nique that anonymizes multiple properties of user observation, e.g. both loca-tion and product association of an observer in the context of consumer price sharing application. To the best of our knowledge, it is the first work which supports multi-dimensional anonymization in PSS. This paper also presents an in-depth analysis of adversary threats considering collusion of adversaries and different report interception patterns. Theoretical analysis, comprehensive simulation, and Android prototype based experiments are carried out to estab-lish the applicability of the proposed scheme. Also, the adversary capability is simulated to prove our scheme’s effectiveness against privacy risk.

FBG Temperature and Pressure Sensing System for Hot Water Pipeline of Petrochemical Factory

A spatial and wavelength division multi- plexing fiber Bragg grating （FBG） sensing system is reported for monitoring the temperature and the pressure （T-P） of hot water pipeline in petrochemieal factory. The FBG sensing system has 72 channels independently, and it provides the capability to monitor large number sensors at same time. A resolution of 0.1℃ and 0.01 MPa with a measurement bandwidth of 150 Hz has been achieved.

Building Feedback-Regulation System Through Atomic Design for Highly Active SO_(2)Sensing

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction.Herein,we present an ingen-ious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO_(2)sensing.We found that the single Pt sites on the MoS_(2)surface can induce easier volatiliza-tion of adjacent S species to activate the whole inert S plane.Reversely,the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms,thus creating a combined system involving S vacancy-assisted single Pt sites(Pt-Vs)to synergistically improve the adsorption ability of SO_(2)gas molecules.Further-more,in situ Raman,ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS_(2)supports in SO_(2)gas atmosphere.Equipped with wireless-sensing modules,the final Pt1-MoS_(2)-def sensors array can further realize real-time monitoring of SO_(2)levels and cloud-data storage for plant growth.Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

Remote sensing of quality traits in cereal and arable production systems:A review

Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multiplatform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.

Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of pictures.This study presents a new approach to the encryption and compression of color images.It is predicated on 2D compressed sensing(CS)and the hyperchaotic system.First,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security.Then,the processed images are con-currently encrypted and compressed using 2D CS.Among them,chaotic sequences replace traditional random measurement matrices to increase the system’s security.Third,the processed images are re-encrypted using a combination of permutation and diffusion algorithms.In addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct images.Compared with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational complexity.Furthermore,it has better robustness.The experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.

Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.

Design and Implementation of a High-Sensitivity Magnetic Sensing System Based on GMI Effect

A high-sensitivity magnetic sensing system based on giant magneto-impedance(GMI)effect is designed and fabricated.The system comprises a GMI sensor equipped with a gradient probe and an signal acquisition and processing module.A segmented superposition algorithm is used to increase target signal and reduce the random noise.The results show that under unshielded,room temperature conditions,the system achieves successful detection of weak magnetic fields down to 2 pT with a notable sensitivity of 1.84×108V/T(G=1000).By applying 17 overlays,the segmented superposition algorithm increases the power proportion of the target signal at 31 Hz from6.89%to 45.91%,surpassing the power proportion of the 2 Hz low-frequency interference signal.Simultaneously,it reduces the power proportion of the 20 Hz random noise.The segmented superposition process effectively cancels out certain random noise elements,leading to a reduction in their respective power proportions.This high-sensitivity magnetic sensing system features a simple structure,and is easy to operate,making it highly valuable for both practical applications and broader dissemination.

Delineation of groundwater potential zones using remote sensing and Geographic Information Systems(GIS)in Kadaladi region,Southern India

The primary objective of this research is to delineate potential groundwater recharge zones in the Kadaladi taluk of Ramanathapuram,Tamil Nadu,India,using a combination of remote sensing and Geographic Information Systems(GIS)with the Analytical Hierarchical Process(AHP).Various factors such as geology,geomorphology,soil,drainage,density,lineament density,slope,rainfall were analyzed at a specific scale.Thematic layers were evaluated for quality and relevance using Saaty's scale,and then inte-grated using the weighted linear combination technique.The weights assigned to each layer and features were standardized using AHP and the Eigen vector technique,resulting in the final groundwater potential zone map.The AHP method was used to normalize the scores following the assignment of weights to each criterion or factor based on Saaty's 9-point scale.Pair-wise matrix analysis was utilized to calculate the geometric mean and normalized weight for various parameters.The groundwater recharge potential zone map was created by mathematically overlaying the normalized weighted layers.Thematic layers indicating major elements influencing groundwater occurrence and recharge were derived from satellite images.2 Results indicate that approximately 21.8 km of the total area exhibits high potential for groundwater recharge.Groundwater recharge is viable in areas with moderate slopes,particularly in the central and southeastern regions.