Monitoring Platform Research Articles

Remote Symptom Alerts and Patient-Reported Outcomes (PROS) in Real-World Breast Cancer Practice: Innovative Data to Derive Symptom Burden and Quality of Life.

Treatment for breast cancer (BC) can lead to debilitating symptoms that can reduce outcomes and quality of life (QoL). Symptom surveillance using a remote symptom monitoring (RSM) platform enables the capture and reporting of patient-reported outcomes (PROs) from home. Women with BC used an RSM platform to complete weekly surveys and report any symptoms experienced during treatment. Symptoms reported as moderate/severe generated alerts to the clinical team. Clinical actions in response to the alert were captured. Results highlighted the value of data generated from a PRO-generated alert system to characterize longitudinal symptom burden and QoL in real-world BC practice, particularly in patients with poor functional status. The most prevalent symptoms that resulted in alerts were pain, nausea/vomiting, neuropathy, fatigue, and constipation. Most women reported one or more moderate/severe symptoms that generated an alert with an average of two alerts per week. Patients with frail status had more alerts, worse QoL and higher treatment bother, indicating that frail patients may benefit from continuous monitoring of symptoms, function, and QoL over time. A case study of patients without pre-existing peripheral neuropathy showed the rapid trajectory from the first report of mild neuropathy until alerts were generated, making a case for early intervention.

Syntheses and Applications of Coumarin-Derived Fluorescent Probes for Real-Time Monitoring of NAD(P)H Dynamics in Living Cells across Diverse Chemical Environments.

Fluorescent probes play a crucial role in elucidating cellular processes, with NAD(P)H sensing being pivotal in understanding cellular metabolism and redox biology. Here, the development and characterization of three fluorescent probes, A, B, and C, based on the coumarin platform for monitoring of NAD(P)H levels in living cells are described. Probes A and B incorporate a coumarin-cyanine hybrid structure with vinyl and thiophene connection bridges to 3-quinolinium acceptors, respectively, while probe C introduces a dicyano moiety for replacement of the lactone carbonyl group of probe A which increases the reaction rate of the probe with NAD(P)H. Initially, all probes exhibit subdued fluorescence due to intramolecular charge transfer (ICT) quenching. However, upon hydride transfer by NAD(P)H, fluorescence activation is triggered through enhanced ICT. Theoretical calculations confirm that the electronic absorption changes upon the addition of hydride to originate from the quinoline moiety instead of the coumarin section and end up in the middle section, illustrating how the addition of hydride affects the nature of this absorption. Control and dose-response experiments provide conclusive evidence of probe C's specificity and reliability in identifying intracellular NAD(P)H levels within HeLa cells. Furthermore, colocalization studies indicate probe C's selective targeting of mitochondria. Investigation into metabolic substrates reveals the influence of glucose, maltose, pyruvate, lactate, acesulfame potassium, and aspartame on NAD(P)H levels, shedding light on cellular responses to nutrient availability and artificial sweeteners. Additionally, we explore the consequence of oxaliplatin on cellular NAD(P)H levels, revealing complex interplays between DNA damage repair, metabolic reprogramming, and enzyme activities. In vivo studies utilizing starved fruit fly larvae underscore probe C's efficacy in monitoring NAD(P)H dynamics in response to external compounds. These findings highlight probe C's utility as a versatile tool for investigating NAD(P)H signaling pathways in biomedical research contexts, offering insights into cellular metabolism, stress responses, and disease mechanisms.

Fast Isolation and Sensitive Multicolor Visual Detection of Small Extracellular Vesicles by Multifunctional Polydopamine Nanospheres.

Small extracellular vesicles (sEVs) assume pivotal roles as vital messengers in intercellular communication, boasting a plethora of biological functions and promising clinical applications. However, efficient isolation and sensitive detection of sEVs continue to present formidable challenges. In this study, we report a novel method for fast isolation and highly sensitive multicolor visual detection of sEVs using aptamer-functionalized polydopamine nanospheres (SIMPLE). In the SIMPLE strategy, aptamer-functionalized polydopamine nanospheres (Apt-PDANS) with 170 nm diameters were synthesized and exhibited a remarkable ability to selectively bind to specific proteins on the surface of sEVs. The binding between sEVs and Apt-PDANS engenders an increase in the overall size of the sEVs, allowing fast isolation of sEVs by filtration (a filter membrane with a pore size of 200 nm). The fast isolation strategy not only circumvents the interference posed by unbound proteins and excessive probes as well as the intricacies associated with conventional ultracentrifugation methods but also expedites the separation of sEVs. Concurrently, the incorporation of Fe3+-doped PDANS permits the multicolor visual detection of sEVs, enabling quantitative analysis by the discernment of visual cues. The proposed strategy achieves a detection limit of 3.2 × 104 sEV mL-1 within 1 h, devoid of any reliance on instrumental apparatus. Furthermore, we showcase the potential application of this methodology in epithelial-mesenchymal transition monitoring and cancer diagnosis, while also envisioning its widespread adoption as a straightforward, rapid, sensitive, and versatile platform for disease monitoring and functional exploration.

Supervised classification and fault detection in grid-connected PV systems using 1D-CNN: Simulation and real-time validation

Photovoltaic (PV) systems are prone to various faults, including short-circuit, open-circuit, partial shading, and inverter bypass diode issues, which reduce power output and can damage components. This study presents an innovative fault detection and online monitoring technique for grid-connected PV (GCPV) systems, combining Internet of Things (IoT) technology with a one-dimensional convolutional neural network (1D-CNN) deep learning approach. The method involves developing a temperature-dependent PV system model using series resistance and ideality factor, capturing real-time data from a 15kWp GCPV system with optimally placed sensors to minimize sensor count while maintaining data accuracy, and validating the model through MATLAB/Simulink simulations and real-time experiments under various fault scenarios. The collected data is used to train the 1D-CNN model to classify different fault types. The model is then implemented on an IoT platform for real-time monitoring and fault detection, displaying system status and alerts via a dashboard. The proposed system achieves a high fault detection accuracy of 98.15 % and 93.12 % during cyberattacks, with an uncertainty of ±4 %, significantly enhancing fault detection reliability and efficiency compared to existing methods. The IoT dashboard provides an effective tool for monitoring system performance and issuing alerts under abnormal conditions.

Planar Disk μ-Aptasensors by Monolayer Assembly in a Dissolving Microdroplet.

Electrochemical aptamer-based sensors provide a highly modular platform for real-time monitoring of small molecules. Their ability to selectively recognize target molecules in complex environments like biological fluids makes them an attractive technology for the analysis of micro- and nanoscale systems. The signal-to-noise of the measurement depends on the electroactive surface (i.e., how many aptamers one can place), which has previously precluded miniaturization of aptamer-based sensors to planar disk ultramicroelectrodes (r ∼ 5-10 μm). Here, we employ a concentration enrichment strategy based on the active dissolution of an aqueous, aptamer-containing microdroplet on an ultramicroelectrode submerged in an organic continuous phase (1,2-dichloroethane). We show consistent voltammetric signal increase as a function of droplet lifetime, indicating the successful immobalization of the thiol-terminated aminoglycoside aptamers to the electrode surface. We observe a diagnostic methylene blue peak and 10-fold increase in current magnitude as compared to bare microelectrodes. We report robust sensor behavior with a linear dynamic range extending from milli- to micromolar concentrations of kanamycin in buffer. This research offers a successful method for optimized electrochemical aptamer-based sensor fabrication and miniaturization on ultramicroelectrodes without the need for electrode surface area enhancement.

Clinical utility of a blood based assay for the detection of IDH1.R132H-mutant gliomas

Glioma represents the most common central nervous system neoplasm in adults. Current classification scheme utilizes molecular alterations, particularly IDH1.R132H, to stratify lesions into distinct prognostic groups. Identification of the single nucleotide variant through traditional tissue biopsy assessment poses procedural risks and does not fully reflect the heterogeneous and evolving tumor landscape. Here, we introduce a liquid biopsy assay, mt-IDH1dx. The blood-based test allows minimally invasive detection of tumor-derived extracellular vesicle RNA using only 2 ml plasma volume. We perform rigorous, blinded validation testing across the study population (n = 133), comprising of IDH1.R132H patients (n = 80), IDH1 wild-type gliomas (n = 44), and age matched healthy controls (n = 9). Results from our plasma testing demonstrate an overall sensitivity of 75.0% (95% CI: 64.1%–84.0%), specificity 88.7% (95% CI: 77.0%–95.7%), positive predictive value 90.9%, and negative predictive value 70.1% compared to the tissue gold standard. In addition to fundamental diagnostic applications, the study also highlights the utility of mt-IDH1dx platform for blood-based monitoring and surveillance, offering valuable prognostic information. Finally, the optimized workflow enables rapid and efficient completion of both tumor tissue and plasma testing in under 4 hours from the time of sampling.

Prototype smart integrated fire detection based on deep learning YOLO v8 and IoT (internet of things) to improve early fire detection

The high incidence of fires in Indonesia in 2018-2023 is 5,336 fire incidents have caused many deaths and enormous material losses. This system is designed to identify early signs of fire through object detection and sensor technology, which is integrated with the Blynk IoT platform for real-time sensor monitoring and Telegram for instant notifications to users. The waterfall prototype method was designed through observation, system design, program code creation, tool testing, and tool implementation. This research uses Deep Learning YOLOv8 technology and IoT using ESP 32 as a microcontroller. Based on the training datasets, it produces precision=0.95872; recall=0.91; mAP50=0.97; mAP50-95 =0.66. The system uses the integration of a multisensor KY-026 flame sensor, DHT 22 temperature and humidity sensor, and MQ-2 sensors can detect CO, LPG, and smoke gas. All these multisensors can be monitored on Blynk IoT and Telegrambot in real time.

Challenges and Solutions for Secure Key Management and Monitoring: Review of the Cerberis3 Quantum Key Distribution System

Quantum Key Distribution (QKD) offers a revolutionary approach to secure communication, leveraging the principles of quantum mechanics to generate and distribute cryptographic keys that are immune to eavesdropping. As QKD systems become more widely adopted, the need for robust monitoring and management solutions has become increasingly crucial. The Cerberis3 QKD system from ID Quantique addresses this challenge by providing a comprehensive monitoring and visualization platform. The system’s advanced features, including central configuration, SNMP integration, and the graphical visualization of key performance metrics, enable network administrators to ensure their QKD infrastructure’s reliable and secure operation. Monitoring critical parameters such as Quantum Bit Error Rate (QBER), secret key rate, and link visibility is essential for maintaining the integrity of the quantum channel and optimizing the system’s performance. The Cerberis3 system’s ability to interface with encryption vendors and support complex network topologies further enhances its versatility and integration capabilities. By addressing the unique challenges of quantum monitoring, the Cerberis3 system empowers organizations to leverage the power of QKD technology, ensuring the security of their data in the face of emerging quantum computing threats. This article explores the Cerberus3 system’s features and its role in overcoming the monitoring challenges inherent to QKD deployments.

Eco-conscious potentiometric sensing: a multiwalled carbon nanotube-based platform for tulathromycin monitoring in livestock products

Tulathromycin (TUL) is a widely used veterinary antibiotic for treating bovine and porcine respiratory infections. Consuming animal-derived food contaminated with this medication may jeopardize human health. This work adopted the first portable potentiometric platform for direct TUL sensing in pharmaceutical and food products. The sensor employed a plasticized PVC membrane on a glassy carbon electrode doped with calix[6]arene and multi-walled carbon nanotubes (MWCNT) in a single solid contact layer for selective binding and signal stability. Characterization via scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) confirmed the material’s integrity. The MWCNT-based sensor produced a stable Nernstian response (1.0 × 10−7 to 1.0 × 10−3 M) and a limit of detection (LOD) of 9.76 × 10–8 M with instantaneous response (8 ± 2 s). IUPAC validation revealed high selectivity for TUL against interfering ions, minimal drift (0.6 mV/h), and functionality over a broad pH range (2.0–7.0), allowing direct application to dosage form, spiked milk, and liver samples. Eco-Scale, AGREE, and Whiteness assessment proved the method's ecological sustainability, economic viability, and practical feasibility, surpassing traditional approaches.Graphical

Spatial mapping of greenhouse gases using a UAV monitoring platform over a megacity in China

Urban environments are recognized as main anthropogenic contributors to greenhouse gas (GHG) emissions, characterized by unevenly distributed emission sources over the urban environments. However, spatial GHG distributions in urban regions are typically obtained through monitoring at only a limited number of locations, or through model studies, which can lead to incomplete insights into the heterogeneity in the spatial distribution of GHGs. To address such information gap and to evaluate the spatial representation of a planned GHG monitoring network, a custom-developed atmospheric sampler was deployed on a UAV platform in this study to map the CO2 and CH4 mixing ratios in the atmosphere over Zhengzhou in central China, a megacity of nearly 13 million people. The aerial survey was conducted along the main roads at an altitude of 150 m above ground, covering a total distance of 170 km from the city center to the suburbs. The spatial distributions of CO2 and CH4 mixing ratios in Zhengzhou exhibited distinct heterogeneities, with average mixing ratios of CO2 and CH4 at 439.2 ± 10.8 ppm and 2.12 ± 0.04 ppm, respectively. A spatial autocorrelation analysis was performed on the measured GHG mixing ratios across the city, revealing a spatial correlation range of approximately 2 km for both CO2 and CH4 in the urban area. Such a spatial autocorrelation distance suggests that the urban GHG monitoring network designed for emission inversion purposes need to have a spatial resolution of 4 km to characterize the spatial heterogeneities in the GHGs. This UAV-based measurement approach demonstrates its capability to monitor GHG mixing ratios across urban landscapes, providing valuable insights for GHG monitoring network design.

3D Hybrid branched carbon/ZnO core-shell nanostructure as biosensor for sensitive and selective detection of glucose

Reliable glucose monitoring at physiological pH and clinical practical range is critical for appropriate diabetes management which remains one of a major health concern. Herein, we describe the construction of flexible and 3D hybrid electrode for glucose sensing by successful immobilization of the GOx on branched carbon/ZnO core–shell nanostructures electrode. The microstructure, morphology and device properties of glucose sensor was systemically characterized by using HRTEM, SEM, FT-IR, and electrochemical analysis. The branched carbon/ZnO core–shell nanostructure sensor showed reliable stability, selectivity and remarkable sensitivity (i.e., 32.48 (±0.04) µA mM−1 cm−2) for glucose in clinical range at physiological pH conditions. The mediator less direct electron communication between the electrode surface and the redox center (FADH & FAD) was also analyzed comprehensively, which concludes an efficient direct electron communication (DET). This enhanced DET can be attributed to the larger surface area provided by the branched carbon/ZnO core–shell nanostructure and also favorable orientation of GOx which allows close proximity of the redox center and the electrode surface. It is believed that such kind of sensors could provide an ideal platform for continuous glucose monitoring (CGM) device fabrication which could perform glucose sensing in real-time and in-vivo analysis.

A comparative study on humidity response of graphene oxide with reduced graphene oxide and its multifunctional applications

In this paper, we present a comparative study of Graphene Oxide (GO) and chemically reduced Graphene Oxide (rGO) based resistive type humidity sensors fabricated on Ti/Au Inter-Digital Electrodes (IDEs) coated SiO2 substrates. The sensing performance, including sensitivity, response/recovery time, and hysteresis has been evaluated for both sensors. The GO film exhibited quick response (0.3 s) and high sensitivity (104.7 kΩ/%RH) with remarkable repeatability and negligible hysteresis as compared to rGO film sensor. The excellent humidity sensing properties of GO are attributed to the presence of abundant oxygen-containing polar functional groups on GO relative to rGO. To demonstrate the multifunctional applications of developed GO based sensor, we have also demonstrated its use as respiratory monitoring, non-contact proximity detector, and speech event detector through the detection of humidity perturbations. The work suggests GO sensitive material has high potential for the development of wearable and integrated health monitoring platforms and non-contact sensing devices.

Efficacy and safety of dynamic arterial elastance for weaning vasopressor support in septic shock patients: a randomised controlled trial protocol

IntroductionThe dynamic arterial elastance (EaDyn), calculated as pulse pressure variation divided by stroke volume variation, has been studied as a predictor of vasopressor weaning. However, its potential as a haemodynamic...

Customized Flexible Osteoid Electrode for Traumatic Brain Injury Induced Posttraumatic Epilepsy Monitoring

AbstractTraumatic brain injury (TBI)‐induced post‐traumatic epilepsy (PTE) is a serious brain disease that causes the loss of motor functions, cognitive impairments, and even death. Real‐time and long‐term electrophysiological signal monitoring has significant implication for the treatment of patient with TBI. Brain–computer interfaces (BCIs) utilizing flexible electrodes enable accurate epilepsy identification by electrocorticography (ECoG) signal monitoring. In this study, a customized flexible osteoid electrode is developed, which contributes to demands and personal differentiation among patients with TBI. The end product of osteoid electrode after full osseointegration will be a stable and firmly integrated structure within the bone tissue, providing a secure platform for continuous electrophysiological signal monitoring. The flexibility and conductivity of the osteoid electrode enables high‐quality and long‐term epilepsy monitoring. Biocompatibility of the osteoid electrode is also demonstrated by in vitro cell experiments. Simultaneously, the porous osteoid electrode also exhibits osseointegration ability based on potential long‐term ECoG signal monitoring, which suggests its potential for the comprehensive treatment of TBI patients. This work not only introduces a potential therapeutic scaffold for TBI‐related diseases, but also provides promising techniques for clinical ECoG monitoring in patients with TBI.

Variations in provider practices in remote patient monitoring on peritoneal dialysis in the USA and Canada.

Automation has allowed clinicians to program PD treatment parameters, all while obtaining extensive individual treatment data. This data populates in a centralized online platform shortly after PD treatment completion. Individual treatment data available to providers includes patients' vital signs, alarms, bypasses, prescribed PD treatment, actual treatment length, individual cycle fill volumes, ultrafiltration volumes, as well as fill, dwell, and drain times. However, there is no guidance about how often or if this data should be assessed by the clinical team members. We set out to determine current practice patterns by surveying members of the home dialysis team managing PD patients across the United States and Canada. A total of 127 providers completed the survey. While 91% of respondents reported having access to a remote monitoring platform, only 31% reported having a standardized protocol for data monitoring. Rating their perceived importance of having a standard protocol for remote data monitoring, on a scale of 0 (not important at all) to 10 (extremely important), the average response was 8 (physicians 7; nurses 9). Most nurses reported reviewing the data multiple times per week, whereas most physicians reported viewing the data only during regular/monthly visits. Although most of the providers who responded have access to remote monitoring data and feel that regular review is important, the degree of its utilization is variable, and the way in which the information is used is not commonly protocolized. Working to standardize data interpretation, testing algorithms, and educating providers to help process and present the data are important next steps.

Ultrasound-responsive theranostic platform for the timely monitoring and efficient thrombolysis in thrombi of tPA resistance

There is no effective and noninvasive solution for thrombolysis because the mechanism by which certain thrombi become tissue plasminogen activator (tPA)-resistant remains obscure. Endovascular thrombectomy is the last option for these tPA-resistant thrombi, thus a new noninvasive strategy is urgently needed. Through an examination of thrombi retrieved from stroke patients, we found that neutrophil extracellular traps (NETs), ε-(γ-glutamyl) lysine isopeptide bonds and fibrin scaffolds jointly comprise the key chain in tPA resistance. A theranostic platform is designed to combine sonodynamic and mechanical thrombolysis under the guidance of ultrasonic imaging. Breakdown of the key chain leads to a recanalization rate of more than 90% in male rat tPA-resistant occlusion model. Vascular reconstruction is observed one month after recanalization, during which there was no thrombosis recurrence. The system also demonstrates noninvasive theranostic capabilities in managing pigs’ long thrombi (>8 mm) and in revascularizing thrombosis-susceptible tissue-engineered vascular grafts, indicating its potential for clinical application. Overall, this noninvasive theranostic platform provides a new strategy for treating tPA-resistant thrombi.

Adherence to Cardiac Rehabilitation in Patients with Acute Myocardial Infarction After PCI: A Scoping Review.

Cardiac rehabilitation (CR) is a multidisciplinary intervention program aimed at enhancing the physical, psychological, and social functioning of patients with cardiovascular disease. Although CR is cost-effective and reduces mortality and readmission rates, and many patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) do not adhere to CR. This review aimed to synthesize the evidence on adherence to CR in patients with AMI after PCI (AMI-PCI). The review was conducted using the methodology proposed by the Joanna Briggs Institute (JBI) to guide reviews and reporting using the Preferred Reporting Items for Systematic Reviews and Meta-analyses Extended for Scoping Reviews (PRISMA-ScR). We searched PubMed, Web of Science, CINAHL, Embase, Ovid, and Scopus databases, and two reviewers independently screened the abstracts and full texts of eligible studies against the inclusion and exclusion criteria. Disagreements were resolved in consultation with a third reviewer. A total of 10 studies were included in the analysis. The results demonstrated that CR reduces the incidence of complications and improves the quality of life of patients with AMI-PCI. However, the CR adherence rate was low, and the factors affecting it are complex and varied, including age, sex, and employment status. Furthermore, interventions to improve adherence in patients with AMI-PCI mainly combined the internet-based interventions, including videoconferencing tele-training, with wearable device monitoring and intelligent management platform follow-up. All these interventions have shown promising results compared with routine care. Adherence to CR in patients with AMI-PCI is generally low, and CR adherence is affected by many factors; however, relevant research designs are rare and simple. Healthcare professionals should pay more attention to adherence to CR in this population and use a variety of interventions to improve it.

“Four - in - one” platform based on multifunctional nanozyme for ultra - accurate detection and on - demand disinfection of Listeria monocytogenes

The inability to integrate detection and disinfection hindered building a unified pathogen monitoring platform, risking secondary contamination. Herein, a novel “four - in - one” platform for monitoring foodborne Listeria monocytogenes (L. monocytogenes) was presented. The magnetic daptomycin - functionalized Fe3O4 (Dap/Fe3O4) could selectively bind to L. monocytogenes, enhancing detection accuracy. The separated bacteria were captured by aptamers - functionalized Fe - doped - silica nanoparticles (Apt/Fe@SiNPs) for tri - mode detection. Besides fluorescence, the Apt/Fe@SiNPs converted 3,3′,5,5′ - tetramethylbenzidine (TMB) to oxidized TMB (oxTMB) via peroxidase activity, allowing colorimetric and subsequent photothermal detection upon irradiation, as low as 2.06 CFU/mL. Magnetic - induced aggregation of Apt/Fe@SiNPs generated toxic hydroxyl radicals around L. monocytogenes, achieving ∼99.6% disinfection. Furthermore, the biofilm of L. monocytogenes was effectively inhibited by the action of hydroxyl radicals. The platform might offer a promising prospect to control L. monocytogenes in food industries.

Spatiotemporal analysis of sand and dust emission point sources detected from satellite imagery in Syria, Jordan, and Iraq

This study utilized MODIS true color satellite imagery to analyse blowing sand and dust events dynamics in the Middle East from 2010 to 2021, focusing on Syria, Iraq, and Jordan. A total of 4923 dust point sources were detected, with a significant concentration (~90 %) located within the Tigris-Euphrates Basin (Nearest Neighbor Ratio = 0.41, р < 0.001). Land cover analysis revealed that bare land, comprising most of the study area, was the predominant source of dust emissions. Wetlands, though only constituting about 1 % of the area, showed the highest frequency of dust sources per unit area, highlighting their role as critical dust emission hotspots. The study emphasizes the impact of drought and anthropogenic factors, such as poor land management, on blowing dust intensity. It suggests the necessity of strategic land management practices, including re-vegetation of arid areas, reducing soil exposure, and implementing wind erosion control measures. To effectively address the transboundary nature of dust emissions, the findings underscore the importance of fostering regional cooperation through mechanisms such as shared environmental monitoring and data exchange platforms, joint management of cross-border natural resources, and collaborative policy making.

The Inversion Location of Microleakage Source and Diffusion Backward Tracing Method Based on 3D Visual Information Model of Salt-Cavern Gas Storage

Summary The safe and stable operation of underground gas storage makes a positive contribution to national energy security. To improve the efficiency of real-time monitoring and early warning of gas leakage accidents at the wellsite of salt-cavern gas storage, an inversion location of the gas microleakage source and a backward tracing method of leakage diffusion are proposed. Through building a 3D visual information model of the salt-cavern gas storage based on building information modeling (BIM) technology and combining it with the advantages of the gas sensors, the real-time inversion location of the microleakage source and diffusion backward tracing in the wellsite can be realized. First, multiple point-type laser methane sensors were used to monitor the leakage of some key zones in real time, and a pan/tilt/zoom (PTZ) scanning laser methane telemeter was used to realize the real-time multidimensional space monitoring on-site from horizontal 360° to vertical 180°. Second, a 3D integrated monitoring platform is established to analyze the gas leakage source by combining the monitoring data and improving the mesh interpolation points. Finally, the whole data and wellsite information are imported into the 3D integrated monitoring platform to realize the inversion location of the microleakage source and the real-time monitoring of the leakage and diffusion state in the whole region. The monitoring precision of gas leakage concentration can be up to 1.0 ppm, and the location distance is within 0.1 m based on the numerical simulation of the 3D model and actual detected data from sensors in the platform. Compared with the technical means of manual assisted leak location, this method effectively solves the difficult problem of leakage monitoring and location accurately in the gas storage and can timely reduce the expansion and impact of leakage accidents.