Signal Strength Research Articles

A Breakthrough Authentication Protocol for Fortifying IoT-Cloud Security

Abstract: Physical layer key generation, leveraging the reciprocity and randomness of wireless fading channels, has garnered significant research interest in recent years. While theoretical studies have demonstrated its potential to generate informationtheoretically secure keys, challenges remain in translating theory into practice. This paper provides an overview of the physical layer key generation process and discusses its practical challenges. Various passive and active attacks are analyzed and evaluated through numerical studies. A new key generation scheme using random probing signals and combining usergenerated randomness with channel randomness is introduced to counteract active attacks. Numerical results demonstrate that the proposed scheme achieves higher security strength than existing schemes using constant probing signals under active attacks. Secret-key generation relying on wireless channel reciprocity is an intriguing solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this paper, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS).

Scanning Probe Microscopies for Characterizations of 2D Materials.

2D materials are intriguing due to their remarkably thin and flat structure. This unique configuration allows the majority of their constituent atoms to be accessible on the surface, facilitating easier electron tunneling while generating weak surface forces. To decipher the subtle signals inherent in these materials, the application of techniques that offer atomic resolution (horizontal) and sub-Angstrom (z-height vertical) sensitivity is crucial. Scanning probe microscopy (SPM) emerges as the quintessential tool in this regard, owing to its atomic-level spatial precision, ability to detect unitary charges, responsiveness to pico-newton-scale forces, and capability to discern pico-ampere currents. Furthermore, the versatility of SPM to operate under varying environmental conditions, such as different temperatures and in the presence of various gases or liquids, opens up the possibility of studying the stability and reactivity of 2D materials in situ. The characteristic flatness, surface accessibility, ultra-thinness, and weak signal strengths of 2D materials align perfectly with the capabilities of SPM technologies, enabling researchers to uncover the nuanced behaviors and properties of these advanced materials at the nanoscale and even the atomic scale.

Investigation of triaxial cables and microdetectors in small field dosimetry.

Small field dosimetry presents unique challenges with source occlusion, lateral charged particle equilibrium and detector size. As detector volume decreases, signal strength declines while noise increases, deteriorating the signal-to-noise ratio (SNR). This issue may be compounded by triaxial cables connecting detectors to electrometers. However, effects of cables, critical for precision dosimetry, are often overlooked. There is a need to evaluate triaxial cable and detector impacts on SNR in small fields. To evaluate the influence of triaxial cables and microdetectors on signal-to-noise ratios in small-field dosimetry. This study also aims to establish the importance of cable quality assurance for measurement accuracy.Six 9.1 m length triaxial cables from different manufacturers were tested with six microdetectors . A 6 MV photon beam (TrueBeam) was used, with a water phantom at 5 cm depth with 0.5×0.5 cm2 to 10×10 cm2 fields at 600 MU/min. Readings were acquired using cable-detector permutations with a dedicated electrometer. Cables had differing connector types, conductor materials, insulation, and diameter. Detectors had various sensitive volumes, materials, typical signals, and bias voltages.
Normalized FOFs showed 13.4% and 4.6% variation across cables for 0.5×0.5 cm2 and 1×1 cm2 fields, respectively. The maximum estimated error between any cable-detector combinations was 0.2%. No consistent FOF trend was observed with increasing cable diameter, likely due to different types of detectors used. However, absolute FOF differences of 0.9% and 0.3% were noted between cables for 0.5×0.5 cm2 and 1×1 cm2 fields, respectively.
Regular triaxial cable quality assurance is critical for precision small field dosimetry. A national protocol is needed to standardize cable evaluations/calibrations, particularly for small signals from modern detectors. This could enhance measurement accuracy and treatment delivery with advanced small-field radiotherapy techniques that promise improved patient outcomes. Further studies should expand detector and cable models tested across institutions to establish robust quality control guidelines.

Wi‐Fi fingerprint‐based indoor location: Multiple fingerprints and multiple classifiers with two‐layer fusion weights

SummaryIndoor location based on Wi‐Fi fingerprint has attracted extensive attention recently, since it only requires a mobile device and existing network; it does not require additional infrastructure and hardware. However, localization using only received signal strength fingerprint is susceptible to dynamic environments and device heterogeneity. Localization using signal strength differences fingerprint and hyperbolic location fingerprint which extracted from received signal strength fingerprint is a powerful measure to overcome the device heterogeneity. Existing fusion‐based methods do not fully use of the mutual fusion function of multiple fingerprints, which leads to low positioning accuracy. In order to further improve the positioning accuracy, we propose a multifingerprint multiclassifier and two‐layer fusion weight positioning model. The proposed approach first creates a multiple fingerprints group by gleaning signal strength differences fingerprint and hyperbolic location fingerprint from received signal strength fingerprint. In order to deal with the accuracy decline caused by a single classifier in complex scenes, three typical classifiers, random forest (RF), K‐nearest neighbor (KNN), and support vector machine (SVM), are adopted, and a fusion weight selection algorithm is proposed to improve the localization accuracy by choosing fusion weights intelligently from the two‐layer fusion weights. Experiment results show that the proposed scheme is effective to resolve device heterogeneity, and the position accuracy is improved about 16.9% and 5.8%, respectively, compared with single fingerprint and classifier schemes. The results show that, compared with the single fingerprint scheme, the position accuracy is improved at least 16.9% and 28.4% for the homogeneous and heterogeneous equipments, respectively; as for the proposed multiclassifier fusion method, it achieves at least 5.8% and 8.7% accuracy improvement for the cases with homogeneous and heterogeneous equipments, respectively, compared with other traditional classifiers such as RF, KNN, and SVM.

Adverse event signal mining and serious adverse event influencing factor analysis of fulvestrant based on FAERS database

Fulvestrant, as the first selective estrogen receptor degrader, is widely used in the endocrine treatment of breast cancer. However, in the real world, there is a lack of relevant reports on adverse reaction data mining for fulvestrant. To perform data mining on adverse events (AEs) associated with fulvestrant and explore the risk factors contributing to severe AEs, providing a reference for the rational use of fulvestrant in clinical practice. Retrieved adverse event report information associated with fulvestrant from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database, covering the period from market introduction to September 30, 2023. Suspicious AEs were screened using the reporting odds ratio (ROR) and proportional reporting ratio methods based on disproportionality analysis. Univariate and multivariate logistic regression analyses were conducted on severe AEs to explore the risk factors associated with fulvestrant-induced severe AEs. A total of 6947 reports related to AEs associated with fulvestrant were obtained, including 5924 reports of severe AEs and 1023 reports of non-severe AEs. Using the disproportionality analysis method, a total of 210 valid AEs were identified for fulvestrant, with 45 AEs (21.43%) not listed in the product labeling, involving 11 systems and organs. The AEs associated with fulvestrant were sorted by frequency of occurrence, with neutropenia (325 cases) having the highest number of reports. By signal strength, injection site pruritus showed the strongest signal (ROR = 658.43). The results of the logistic regression analysis showed that concurrent use of medications with extremely high protein binding (≥ 98%) is an independent risk factor for severe AEs associated with fulvestrant. Age served as a protective factor for fulvestrant-related AEs. The co-administration of fulvestrant with CYP3A4 enzyme inhibitors did not show statistically significant correlation with the occurrence of severe AEs. Co-administration of drugs with extremely high protein binding (≥ 98%) may increase the risk of severe adverse reactions of fulvestrant. Meanwhile, age (60–74 years) may reduce the risk of severe AEs of fulvestrant. However, further clinical research is still needed to explore and verify whether there is interaction between fulvestrant and drugs with high protein binding through more clinical studies.

Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds

Abstract. We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere (i.e. between layers or outside a cloud system). Despite the fact that the strength of lidar signals from the molecular atmosphere is much lower compared to the in-cloud intervals, studies of MS effects in such regions are of interest from scientific and practical points of view. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view (RFOV). Therefore, the photons scattered within the forward peak escape the sampling volume formed by the RFOV (i.e. the escape effect). We demonstrated that the escape effect is an inherent part of MS properties within the free atmosphere beyond the cloud far edge. In the cases of the ground-based lidar, the MS contribution is lower than 5 % within the regions of the cloud-free molecular atmosphere with a distance from the cloud far edge of about 1 km or higher. In the cases of the space-borne lidar, the rate of decrease of the MS contribution is so slow that the threshold of 5 % can hardly be reached. In addition, the effect of non-uniform beam filling is extremely strong. Therefore, practitioners should employ, with proper precautions, lidar data from regions below the cloud base when treating data of a space-borne lidar. In the case of two-layered cloud, the distance of 1 km is sufficiently large so that the scattered photons emerging from the first layer do not affect signals from the second layer when we are dealing with the ground-based lidar. In contrast, signals from the near edge of the second cloud layer are severely affected by the photons emerging from the first layer in the case of a space-borne lidar. We evaluated the Eloranta model (EM) in extreme conditions and showed its good performance in the cases of ground-based and space-borne lidars. At the same time, we revealed the shortcoming that can affect practical applications of the EM. Namely, values of the key parameters – i.e. the ratios of phase functions in the backscatter direction for the nth-order-scattered photon and a singly scattered photon – depend not only on the particle phase function but also on the distance from a lidar to the cloud and the receiver field of view. Those ratios vary within a quite large range, and the MS contribution to lidar signals can be largely overestimated or underestimated if erroneous values of the ratios are assigned to the EM.

Photon counting based pump-probe technique for quantitative characterization of fluorescence in a lock-in free detection manner

The stimulated emission (SE) signal in pump-probe experiment is conventionally measured with lock-in detection to differentiate the weak signals from the relatively large background of spontaneous emission and probe beam. Therefore, direct characterization of signal strength are often major limiting factors in terms of noise, speed, and data acquisition. In contrast, photon counting allows direct quantification of signal strength, while synchronized pump-probe pulse enables precise timing and the separation of signals accordingly. Herein, the SE based pump-probe method is combined with time-correlated single-photon counting to investigate the ultrafast photochemical parameters, digitally and quantitatively. As a proof-of-concept, our technique is applied to investigate, fluorescence lifetime (τ)∼3.71ns , optical absorption cross-section (σabs)∼1.23×10−16cm2 , and the SE cross-section (σSE)∼2.22×10−17cm2 , of a fluorescent dye (ATTO 647N) quantitatively. The experimental results are also compared with theoretical photon statistics to further justify the advantages including experimental and statistical critical molecular dynamics parameters extraction with excellent high accuracy.

A nano-imprinted graphene oxide-cellulose composite as a SERS active substrate.

Cellulose is a sustainable material capable of forming optically active nanoarrays on its surface. We created a composite of cellulose acetate (CA) and graphene oxide (GO), by mixing GO (0.1 mg mL-1) into CA. This was then imprinted with nanoscale surface features that form Bragg-like modes in resonance with the excitation laser when a thin layer of silver is vapor deposited onto the surface of the substrate. The addition of GO leads to improved surface-enhanced Raman scattering (SERS) signal strengths, obtaining an average SERS signal increase of 1.4-fold following the inclusion of GO. The combination of photonic and electromagnetic effects with charge transfer-based processes that support the SERS chemical mechanism and the possible presence of electromagnetic hot spots from the roughened surface results in an enhanced SERS signal strength when GO is added. This work shows the potential for nanoimprinted graphene oxide/cellulose acetate composites as flexible sensor platforms to detect target molecules.

Oil Prices and International Conflict: Why Low Oil Revenue May Not Pacify Petrostates1

This article explores how declining oil revenue might shape the amount of international conflict initiated by major oil producers (petrostates). We analyze four potential mechanisms through which variation in oil prices could affect petrostate conflict initiation: emboldenment, battling over a smaller market, signaling strength, and diversionary conflict. The empirical findings suggest that higher oil prices are associated with lower rates of petrostate conflict initiation. From one standard deviation below the mean oil price to one standard deviation above it, the predicted number of militarized interstate disputes declines twofold, from .025 [95% CI: .016–.034] per petrostate per year to .012 [.007–.016]. Moreover, the evidence suggests that petrostates are more likely to target other petrostates when oil prices are low. This suggests that the energy transition may not be a boon for international peace among petrostates, and for a time, it may even prove to be the opposite.

Research on partial discharge detection based on distributed optical fiber acoustic sensor

Distributed acoustic sensors (DASs) have the advantage of long-distance and distributed monitoring of vibration signals. However, there are few studies on the application of DAS for partial discharge (PD) monitoring of power equipment. There is also a lack of related theoretical and methodological studies. In this paper, the DAS-measured phase signals are theoretically analyzed from the frequency and energy perspectives, and the method of PD broadband signal coverage using spectrum and energy accumulation is proposed. Fiber optic rings are employed for the detection of PD signals, and the precise localization of these signals is achieved by calculating the DAS energy spectrum. The fiber optic ring is wrapped around the cable joint to achieve the detection and locating of the PD signal. The results indicate that the use of a fiber optic ring can realize the sensitive detection and locating of PD. The signal strength is maximum when the length of the fiber ring is equal to the spatial resolution of DAS. The sensitivity of PD detection in cable joints can reach 40 pC, and the simultaneous detection and localization of PD at different locations can be realized. The research can provide support for theoretical and experimental for the monitoring of PD in power equipment.

A reflective textile metasurface for indoor signal coverage enhancement

The design of a reflective metasurface solely based on flexible textile material is presented for indoor signal coverage enhancement in a specific scenario – reflecting and reallocating radio frequency energy that would have leaked through a large window area. The proposed reflective metasurface design, reflective metasurface is composed of layers of square conductive textile patches and dielectric textile substrates. For the unit cell design, a reflective phase difference of up to 90° can be achieved via varying the size of the conductive patches. Meanwhile, a phase difference of up to 180° can be achieved by the alignment of conductive patches on different textile substrate layers, which is an ideal design philosophy for textile material. The proposed metasurface, consisting of 12 × 12 unit cells, can achieve a main reflected beam pointing in the direction of ±35° and a secondary reflected beam at ±63°. Simulated results show that the reflected beams remain relatively stable under the crumpling conditions often seen for curtains. A prototype of the design was fabricated and tested in a real-world scenario. A maximum signal strength enhancement of 15 dB and an average enhancement of 5.97 dB in a wide range of directions can be achieved with the reflective metasurface applied.

Impact of Single-Melamine Tautomerization on the Excitation of Molecular Vibrations in Inelastic Electron Tunneling Spectroscopy.

Vibrational quanta of melamine and its tautomer are analyzed at the single-molecule level on Cu(100) with inelastic electron tunneling spectroscopy. The on-surface tautomerization gives rise to markedly different low-energy vibrational spectra of the isomers, as evidenced by a shift in mode energies and a variation in inelastic cross sections. Spatially resolved spectroscopy reveals the maximum signal strength on an orbital nodal plane, excluding resonant inelastic tunneling as the mechanism underlying the quantum excitations. Decreasing the probe-molecule separation down to the formation of a chemical bond between the melamine amino group and the Cu apex atom of the tip leads to a quenched vibrational spectrum with different excitation energies. Density functional and electron transport calculations reproduce the experimental findings and show that the shift in the quantum energies applies to internal molecular bending modes. The simulations moreover suggest that the bond formation represents an efficient manner of tautomerizing the molecule.

Abrocitinib-associated adverse events: a real-world pharmacovigilance study using the FAERS database

ABSTRACT Background Atopic dermatitis (AD) is a common chronic inflammatory skin disease. Janus kinase (JAK) modulates cytokines involved in AD pathophysiology, and JAK inhibitors have emerged as effective pharmacotherapeutic remedies for AD. Abrocitinib, an oral selective inhibitor of JAK1, is indicated for the management of moderate-to-severe AD. The current study evaluated the adverse events (AEs) associated with abrocitinib in a real-world setting. Methods To quantify the signals of abrocitinib-associated AEs, we used the US Food and Drug Administration Adverse Event Reporting System (FAERS) for this pharmacovigilance study with two established pharmacovigilance methods. Results A total of 1071 AEs of abrocitinib were investigated as the primary suspected from the FAERS to detect and characterize relevant safety signals. The analysis revealed 85 signals for abrocitinib. The most common AE for abrocitinib was drug ineffective. The signal strength of eczema herpeticum was 515.87 (277.80–957.98) and 510.59 (5148.65) and exhibited the highest strength for abrocitinib. Rare AEs such as aggravated condition, pruritus, and hypersensitivity were not listed on the label, and attention to these AEs is required. Conclusion The analysis of the AE signals may provide support for clinical monitoring and risk identification of abrocitinib.

Mitigating the bullwhip effect through supply chain ESG transparency: roles of digitalization and signal strength

PurposeThe call for supply chain transparency (SCT), especially the environmental, social and governance (ESG) aspect, is getting increasingly louder. Based on the signaling theory, our study investigates the operational benefit of supply chain transparency in terms of ESG (SCT-ESG). To further clarify the signaling process, the moderating roles of digitalization of the firm and signal strength are also examined.Design/methodology/approachLongitudinal secondary data from multiple databases are matched and analyzed using ordinary least squares (OLS) regressions to validate the proposed hypotheses.FindingsResults suggest that with SCT-ESG, firms have a weakened disparity between production variance and demand variance, and the supply chain experiences a reduced bullwhip effect. Further, digitalization of the focal company and signal strength reinforce the negative effect of SCT-ESG on the bullwhip effect.Originality/valueThe study integrates the SCT and ESG literature through SCT-ESG, extending benefits of ESG disclosure to the supply chain context. It extends the application of the signaling theory in OSCM by including contextual factors of digitalization and signal strength.

Initial Study of Adaptive Threshold Cycle Slip Detection on BDS/GPS Kinematic Precise Point Positioning during Geomagnetic Storms

Global navigation satellite system (GNSS) provides users with all-weather, continuous, high-precision positioning, navigation, and timing (PNT) services. In the operation and use of GNSS, the influence of the space environment is a factor that must be considered. For example, during geomagnetic storms, a series of changes in the Earth’s magnetosphere, ionosphere, and upper atmosphere affect GNSS’s positioning performance. To investigate the positioning performance of global satellite navigation systems during geomagnetic storms, this study selected three geomagnetic storm events that occurred from September to December 2023. Utilizing the global positioning system (GPS)/Beidou navigation satellite system (BDS) dual-system, kinematic precise point positioning (PPP) experiments were conducted, and the raw observational data from 100 stations worldwide was analyzed. The experimental results show that the positioning accuracy of some stations in high-latitude areas decreases significantly when using the conventional Geometry Free (GF) cycle-slip detection threshold during geomagnetic storms, which means that the GF is no longer applicable to high-precision positioning services. Meanwhile, there is no significant change in the satellite signal strengths received at the stations during the period of the decrease in positioning accuracy. Analyzing the cycle-slip rates for stations where abnormal accuracy occurred, it was observed that stations experiencing a significant decline in positioning accuracy exhibited serious cycle-slip misjudgments. To improve the kinematic PPP accuracy during magnetic storms, this paper proposes an adaptive threshold for cycle-slip detection and designs five experimental strategies. After using the GF adaptive threshold, the station positioning accuracy improved significantly. It achieved the accuracy level of the quiet period, while the cycle-slip incidence reached the average level. During magnetic storms, the ionosphere changes rapidly, and the use of the traditional GF constant threshold will cause serious cycle-slip misjudgments, which makes the dynamic accuracy in high latitude areas and some mid-latitude areas uncommon, while the use of the GF adaptive threshold can alleviate this phenomenon and improve the positioning accuracy in the high-latitude regions and some of the affected mid-latitude areas during the magnetic storms.

Is restricting mobile communication a solution to overcrowding? A test from Yala National Park, Sri Lanka

The Yala National Park is the premier protected area in Sri Lanka. Overcrowding has been an issue in Yala for over a decade. Information sharing by mobile communication was thought to result in safari jeeps flocking to favoured sightings, causing overcrowding and reckless driving. We assessed visitor satisfaction and the impact of switching off mobile communication towers providing park coverage, by conducting a questionnaire survey, checking signal strength and assessing vehicle speed. We found that visitor satisfaction was related to sightings of the ‘big three’, elephants, leopards and sloth bears, but not to overcrowding at sightings. Reckless driving impacted visitor satisfaction both negatively and positively. High speed driving was mostly due to trying to exit the park before the park-closure time. Switching off mobile communication towers reduced signal strength and accessibility but did not eliminate it. Reduced mobile coverage lessened overcrowding at sightings but also decreased sightings, resulting in an overall reduction of visitor satisfaction. We conclude that reducing or eliminating mobile communication is not a viable solution to overcrowding.

An efficient estimator for source localization in WSNs using RSSD and TDOA measurements

Range-based localization has received considerable attention in wireless sensor networks due to its ability to efficiently locate the unknown source of a signal. However, the localization accuracy with a single set of measurements may be inadequate, especially in dynamic and noisy environments. To mitigate this problem, received signal strength difference (RSSD) and time difference of arrival (TDOA) measurements are used to develop an efficient estimator to reduce the bias and improve localization accuracy. First, the RSSD/TDOA-based maximum likelihood (ML) localization problem is transformed into a hybrid information nonnegative constrained least squares (HI-NCLS) framework. Then, this framework is used to develop an effective bias-reduction localization approach (BRLA) with a two-step linearization process. The first step employs a linear solving method (LSM) which exploits an active set method to obtain a sub-optimal estimator. The second step uses a bias reduction method (BRM) to mitigate the correlation from linearization and a weighted instrumental variables matrix (IVM) which is weakly correlated with the noise but strongly correlated with the data matrix (DM) is used in place of the DM. Performance results are presented which demonstrate that the proposed BRLA provides better localization performance than state-of-the-art methods in the literature.

Distributed Embedded System for Air Quality Monitoring based on Long Range (LoRa) Technology

This study addresses the persistent challenge of urban air quality deterioration through the introduction of the Distributed Embedded System (DES). In response to limitations associated with conventional air quality measurement methods, the DES system offers a cost-effective and portable alternative for real-time monitoring. The study focuses on implementing a low-cost distributed system and developing effective communication protocols between sensor nodes. Equipped with Metal Oxide Semiconductor (MOS) sensors for pollutant gases, optical sensors for particulate matter, and meteorological sensors, the system strategically deploys multiple nodes within a 4 km range of urban areas. Real-time AQI and pollution severity have been measured for various locations. Implementation of Long Range (LoRa) communication technology allows the sensor nodes to efficiently transmit data to a central base station. Observations of received signal strength and signal quality indicate reliable and effective communication. To validate accuracy and reliability, acquired DES system data undergoes comparative analysis with data from a government-established meteorological station, revealing a strong correlation. This innovative approach presents a promising solution for widespread, continuous, and cost-effective real-time air quality monitoring in urban areas. The DES system addresses key challenges associated with air pollution, offering a portable and accessible tool that could revolutionize urban air quality management.

Application of optimization algorithm for virtual reference tag assisted localization and tracking of RFID

SummaryIn an indoor setting, the radio frequency communication is utilized to locate and track mobile objects utilizing Radio Frequency Identification (RFID) technology. Measurements from the Received Signal Strength Indicator (RSSI) are typically the foundation of the localization technique. In an RFID‐based interior setting, lowering tracking mistakes and increasing the precision of tracking remain difficult tasks. In order to address these issues, we developed the VIRALTRACK (Virtual Reference Tag Localization and Tracking) framework that consists of four procedures: deep reinforced learning‐based tracking, quantum‐based localization, optimization‐based virtual reference tag allocation, and signal enhancement. In order to increase the signal's effectiveness, we initially suggested using the Extended Gradient Filter (EGF) technique to eliminate RSSI oscillations. In the second step, we suggested using the Emperor Penguin Colony (EPC) optimization technique to allocate the virtual reference tag while taking the number of tags, SNR, and temperature and humidity of the surroundings into account. In the third phase, we use a quantum neural network (QNN) for localization in order to estimate the position of the moving target. We introduced the SignRank approach to select the best virtual reference tag for localization, which lowers tracking mistakes. In conclusion, we presented the Twin Delayed Deep Deterministic Policy Gradient (TD3) method that boosts the tracking precision by tracking the moving target tag efficiently and taking into account stage, the orientation, distance, and valuable coordinates. The NS3.26 network simulator is used to run the simulation, and tracking precision, tracking error, and accumulated probabilities are used to assess effectiveness.

Mobility target tracking with meta‐heuristic aided target movement prediction scheme in WSN using adaptive distributed extended Kalman filtering

SummaryIn wireless sensor networks (WSNs), target tracking has been prominently raised in recent days. Because of the frequent utilization of WSN, the attention on target tracking is greatly increased. The estimated optimal value derived from the earlier moment is rarely taken into consideration in traditional target‐tracking algorithms. One of the most crucial uses of WSNs is mobile target tracking, and it is especially used for spying. Precision surveillance is heavily dependent on localization or distance estimation, and extensive study has been done in this area. This research aims to develop a new target‐tracking network‐assisted target movement prediction model in WSN with reduced energy consumption. The major phases involved in the proposed target movement prediction in WSN are (a) mobility target tracking and (b) target movement prediction. Initially, the mobility target tracking is done with the help of adaptive distributed extended Kalman filtering (ADEKF). The mobility target tracking performance is improved by optimally tuning the parameters from ADEKF with the support of the improved squid game optimizer (ISGO). Then, the target movement prediction phase is executed with the help of input parameters like “Angle of Arrival (AoA) and Received Signal Strength (RSS),” and the optimal progress of the mobile node is predicted. The implementation outcome of the proposed tracking network‐assisted target movement prediction model is validated concerning various performance metrics. Overall performance analysis shows that the developed model offers 2.5% in terms of RMSE measures. The developed model shows better analysis while validating with existing approaches.