Conventional Techniques Research Articles

Evaluation of risk factors associated with hard-to-heal wound infection in a tertiary care hospital.

The incidence of hard-to-heal wound infection, especially as a result of multidrug-resistant Gram-negative organisms, has increased in recent years. The reason for the increase is multifactorial and the ability of these pathogenic isolates to form biofilms is one of the important risk factors in wound infection. This study aimed to evaluate the risk factors associated with such cases. This prospective analytical study, conducted over a period of two months, included pus or tissue samples from hospital inpatients with Gram-negative hard-to-heal wound infection. The samples were processed with conventional microbiological techniques. Patient demographic details and the presence of various risk factors were recorded. Biofilm production was detected by tissue culture plate method in the laboratory. The data were analysed using SPSS version 21 (IBM Ltd., US). The experimental cohort comprised 200 patients. Klebsiella spp. was the most common identified organism, followed by Escherichia coli and Pseudomonas spp. Carbapenem resistance was observed in 106 (53%) strains. Almost 66% of the strains showed biofilm formation. On evaluation of associated risk factors, age (p=0.043), presence of biofilms (p=0.0001), diabetes (p=0.002), hypertension (p=0.02) and medical device use (p=0.008) had significant association, whereas sex, previous surgery and prior antibiotic use had no significant impact on the chronicity of the wound. In this study, chronicity of wounds was observed to be associated with multiple risk factors, especially the biofilm-forming ability of the strain. Biofilms are difficult to eradicate and additional measures, such as physical debridement, are important for resolving chronicity. Knowledge about specific risk factors would also allow clinicians a better understanding of the healing process and drive appropriate wound care interventions. A grant was received from the Indian Council of Medical Research (ICMR) for this work (grant ID: 2017-02686). The authors have no conflicts of interest to declare.

Factors associated with decreased length of stay following robotic arm-assisted and conventional total hip arthroplasty.

Postoperative length of stay (LOS) and discharge dispositions following arthroplasty can be used as surrogate measurements for improvements in patients' pathways and costs. With the increasing use of robotic technology in arthroplasty, it is important to assess its impact on LOS. The aim of this study was to identify factors associated with decreased LOS following robotic arm-assisted total hip arthroplasty (RO THA) compared with the conventional technique (CO THA). This large-scale, single-institution study included 1,607 patients of any age who underwent 1,732 primary THAs for any indication between May 2019 and January 2023. The data which were collected included the demographics of the patients, LOS, type of anaesthetic, the need for treatment in a post-anaesthesia care unit (PACU), readmission within 30 days, and discharge disposition. Univariate and multivariate logistic regression models were used to identify factors and the characteristics of patients which were associated with delayed discharge. The multivariate model identified that age, female sex, admission into a PACU, American Society of Anesthesiologists grade > II, and CO THA were associated with a significantly higher risk of a LOS of > two days. The median LOS was 54 hours (interquartile range (IQR) 34 to 78) in the RO THA group compared with 60 hours (IQR 51 to 100) in the CO THA group (p < 0.001). The discharge dispositions were comparable between the two groups. A higher proportion of patients undergoing CO THA required PACU admission postoperatively, although without reaching statistical significance (7.2% vs 5.2%, p = 0.238). We found that among other baseline characteristics and comorbidities, RO THA was associated with a significantly shorter LOS, with no difference in discharge destination. With the increasing demand for THA, these findings suggest that robotic assistance in THA could reduce costs. However, randomized controlled trials are required to investigate the cost-effectiveness of this technology.

Pharmaceuticals in the Water: Emerging Concerns and Innovative Remediation Solutions

Abstract: Pharmaceutical contamination, resulting from the discharge of active pharmaceutical ingredients (APIs) and other related compounds into the water, has become a growing concern due to its potential adverse effects on ecosystems and human health. This review article aims to examine the many facets of pharmaceutical contamination and highlight the most recent developments in its remediation. The effects of pharmaceuticals, sources, and pathways of pharmaceutical contamination, as well as the difficulties in detecting and evaluating its toxicities, have been included in the present manuscript. Nowadays various remediation strategies are employed to mitigate pharmaceutical contamination in water. Conventional wastewater treatment techniques, including activated sludge processes and membrane filtration, are effective in removing a portion of the pharmaceutical compounds. However, advanced oxidation processes such as ozonation and photocatalysis have shown promising results in enhancing the degradation of recalcitrant APIs. Nanotechnology-based approaches, such as the use of nanoparticles for adsorption and degradation, and bioremediation methods utilizing microbial degradation, enzymatic processes, and phytoremediation, offer potential future directions for efficient and sustainable remediation. This review describes the most recent developments, current status, and potential research directions with the future prospects of pharmaceutical pollutants.

Printing of liquid metal by electrically modulating of interface tension in liquid environment

In recent years, gallium-based liquid metal has emerged as a prominent research material in the realm of flexible electronics, owing to its exceptional electrical conductivity and deformability. The crux of developing flexible electronic devices using liquid metal as a conductive material lies in the patterning of the liquid metal. Inkjet printing technology possesses the capability to efficiently craft functional patterns by printing any inkable material. However, due to the facile oxidation of the gallium-based liquid metal surface in ambient air, leading to the formation of oxide films and the presence of high surface tension, conventional inkjet printing techniques are incapable of directly rendering liquid metal prints. This manuscript introduces a refined and remarkably efficient approach to inkjet printing utilizing the liquid metal. By deftly adjusting the interfacial tension of the liquid metal at the nozzle with ultra-low potentials, falling within the 2-V range, the achievement of on-demand, micron-scale liquid metal microdroplet ejection printing surpassing 3 kHz is brought to fruition. This article delves into unraveling the mechanisms of potential modulation on the interfacial tension of the liquid metal at the nozzle, as well as the fundamental theories pertaining to the formation and migration of liquid metal microdroplets. These insights establish a theoretical and technical foundation for the application of liquid metals in the field of electronic printing.

A linear cross-coupled gate-driven quasi-floating bulk low-power wide input range transconductor.

High linearity for a wider input voltage range and low-power operation of the operational transconductance amplifier (OTA) are indispensable parameters for health care applications, which require high quality and accurate signal conditioning. However, achieving low-power operation along with high linearity at low supply voltages is challenging for OTA using conventional low-power and linearization techniques. This paper proposes an OTA based on a cross-coupled gate-driven quasi-floating bulk (CGDQFB) MOSFET and source-degenerated linearization techniques, which works at a supply of ±0.5V. The post-layout simulations of the proposed OTA are performed in the 180nm standard CMOS process, which shows a transconductance of 0.321 μS, an output impedance of 331 MΩ, an input impedance of 897 GΩ, a DC gain of 40.54 dB, a gain-bandwidth of 0.145MHz, a total harmonic distortion (THD) of 51.09 dB for an input voltage range of 626.7 mV at a frequency of 100.39Hz, and a power consumption of 0.45 μW. The proposed OTA shows an input common mode range of -0.34 to 0.4V, an output voltage swing of -0.34 to 0.34V, a common mode rejection ratio of 91.08 dB, and a consumption area of 23 965.92 µm2. Furthermore, with 200 Monte Carlo iterations, the proposed OTA shows variability for gain and THD of 0.003 and 0.036, respectively. The proposed CGDQFB OTA is a suitable contender for conditioning bio-signals used in health care applications.

An efficient MPPT techniques for inter-harmonic reduction in grid connected hybrid wind and solar energy systems

In this work, the operation of photovoltaic system, wind turbine driven doubly fed induction generator along with battery has been observed. Also, a searching space minimization-based artificial bee colony scheme is developed for tracking the maximum power in a doubly fed induction generator-based system. To track maximum power in solar systems, an improved adaptive reference voltage approach has been presented. Several conventional and optimization-based techniques are used by DFIG and photovoltaic systems to get around the non-linearity features in the output parameters. Regarding DFIG, the artificial bee colony method based on searching space minimization can be used to solve the shortcomings of the perturb and observe algorithm. Because of its weather-sensitive nature, it can withstand sudden changes in wind speed. The suggested searching space minimization based artificial bee colony strategy uses a mechanism for determining the range of optimal rotor speed in order to track the maximum power point more quickly. The maximum power point tracking performance of the adaptive reference voltage technique is superior to that of current perturb and observed-based systems. However, a huge processing memory is required in order to track the maximum possible power point. This paper proposes an enhanced maximum power point tracking technique based on adaptive reference voltage that does not require a memory unit. Additionally, despite sudden changes in irradiation conditions, improved adaptive reference voltage can drift-free and reliably monitor the maximum power point. The new adaptive reference voltage technique uses temperature and radiation sensors to identify the region nearest to the maximum power point. This helps the system respond more quickly. The proposed system with searching space minimization based artificial bee colony and improved adaptive reference voltage schemes displays lower inter-harmonic content in grid current compared to perturb and observe scheme. The proposed scheme has been implemented in MATLAB & simulink atmosphere and OPAL-RT displayed satisfactory results.

Federated learning enables 6 G communication technology: Requirements, applications, and integrated with intelligence framework

The 5 G networks are effectively deployed worldwide, and academia and industries have begun looking at 6 G network communication technology for consumer electronics applications. 6 G will be built on pervasive artificial intelligence (AI) to enable data-driven Machine Learning (ML) applications in massively scalable and heterogeneous networks. Conventional ML technique involves centralizing train data in data centers where centralized ML algorithms can be employed for data inference and analysis. The data inference and analysis are frequently inconvenient or impracticable for the devices to submit information to the preset sever because of privacy concerns and inadequate communication capabilities in wireless networks. However, privacy limitations and restrictions in wireless network communication capacity are frequently impractical or undesirable for the devices to acquiesce data to the parameter server. Federated learning (FL) enables the devices to train a practical and standard model while needing data exchange and transfer, which might solve these issues. This paper presents an overview of FL, 6 G, and FL enables 6 G communication technology. In particular, 6 G requirements and applications, and the proposed FL framework algorithm with evaluation are described. Finally, FL-enabling 6 G communication technologies open challenges, and research directions are discussed to help future researchers improve the FL-enabled 6 G network.

Synthetic Modifications of a Pb2+-Sensor Acridono-Crown Ether for Covalent Attachment and Their Effects on Selectivity.

Because of environmental impact, there is a great need for chemosensors, especially for toxic heavy metals such as lead. The conventional instrumental analytical techniques rarely provide an available real-time sensing platform, thus the development of highly selective and stable synthetic chemosensor molecules is of great importance. Acridono-18-crown-6 ethers have such properties, and much research has proven their outstanding applicability in various supramolecular devices. In this present work, we aimed to enable their covalent immobilization capability by synthesizing functionalized derivatives while preserving the favored molecular recognition ability. Several new macrocycle analogues were synthesized, while synthetization difficulties and design aspects were also dealt with. The selectivity of the macrocycle analogues was studied using UV-Vis spectroscopy and compared with that of the parent compounds. The ultimate crown ether derivative showed high Pb2+-selectivity, reversibility (decomplexation by extraction with water) and stability.

Accurate surgical posterior tibial slope alteration can be achieved in total knee arthroplasty regardless of surgeon skill level or local soft tissue thickness-A retrospective radiograph-based study.

To retrospectively report on the impact of local soft tissue thickness and surgeon skill level on the accuracy of surgical posterior tibial slope (PTS) alteration achieved in patients undergoing total knee arthroplasty (TKA) utilising lateral knee radiographs. Pre- and postoperative radiographs of 82 patients undergoing primary TKA using conventional mechanical alignment technique were measured by two observers and subjected to quality criteria for accurate measurement of the PTS. All patients underwent a standardised surgical approach for PTS alteration: cruciate-retaining (CR) cases with preoperative PTS ≤ 10° were set for reconstruction of the preoperative PTS. Cases indicated for posterior-stabilised (PS) design and/or with a preoperative PTS > 10° were set for 3° of postoperative PTS. Pretibial subcutaneous fat (PSF) and surgeon skill level were analysed for their predictive quality regarding the accuracy of surgical PTS alteration achieved. The overall mean postoperative PTS was significantly lower than the preoperative values (6.2°, SD 2.7 vs. 7.7°, SD 3.2; p = 0.002103). Neither local soft tissue thickness, namely PSF, nor surgeon skill level was found to be a predictor of the accuracy of surgical PTS alteration achieved. Among cases set for PTS reconstruction, 25.9% and 42.6% achieved a postoperative PTS within ±1° and ±2° of preoperative values, respectively. In patients with a PTS > 10° or those indicated for PS design, slope reduction was achieved with a mean postoperative PTS of 6.5°. Furthermore, 14.3% and 32.1% of cases were within ±1° and ±2° of 3, respectively. This study demonstrates that accurate surgical alteration of the PTS is possible in TKA regardless of local knee soft tissue thickness or surgeon skill level. This proves the clinical feasibility of both targeted reduction as well as reconstruction of the PTS in TKA. Level III, retrospective cohort study.

Monitoring of general anesthesia by qCON and qNOX indices versus conventional clinical parameters in urological surgery: A randomized controlled clinical trial

Background: Awareness during anesthesia is a major anesthetic concern. Depth of anesthesia is commonly assessed in clinical practice by the patient’s clinical signs and symptoms such as blood pressure, heart rate variability, and body movement. At present, many studies have focused on qCON monitoring for sedative depth, but only a few studies have focused on qNOX monitoring for analgesic depth. Aims and Objectives: The aim of the present study was to evaluate the relative efficacy of qCON and qNOX versus commonly used vital signs such as blood pressure and heart rate in monitoring the anesthetic depth and analgesia. Materials and Methods: A total of 100 patients of either sex and of ASA Physical status I &amp; II, scheduled for urogenital surgeries, were selected and randomly placed into two groups. Group A was monitored by conventional clinical technique and Group B was monitored by qCON and qNOX indices. The primary outcome was the total dose of propofol and fentanyl required to maintain the depth of anesthesia and analgesia. The secondary outcomes were propofol and fentanyl adjustment frequency, infusion duration, and quality of recovery from anesthesia. Results: Results showed statistically significant differences between the two groups in mean dose of both propofol (P=0.000) and fentanyl (P=0.006), adjustment frequency of both propofol (P=0.000) and fentanyl (P=0.010), time required to voluntary eye-opening (P=0.000) and extubation time (P=0.000) and visual analog scale score (P=0.000). There was no statistically significant difference found in infusion duration (P=0.317) and Ramsay Sedation Score (P=0.709) between the groups. Conclusion: Using the qCON and qNOX indices, an anesthesiologist can monitor the depth of anesthesia and analgesia more effectively and can adjust the anesthetic or analgesic drug dosing in a better possible way with lesser requirement of drugs than with conventional clinical monitoring.

Recent Advances in Conventional and Deep Learning-Based Depth Completion: A Survey.

Depth completion aims to recover pixelwise depth from incomplete and noisy depth measurements with or without the guidance of a reference RGB image. This task attracted considerable research interest due to its importance in various computer vision-based applications, such as scene understanding, autonomous driving, 3-D reconstruction, object detection, pose estimation, trajectory prediction, and so on. As the system input, an incomplete depth map is usually generated by projecting the 3-D points collected by ranging sensors, such as LiDAR in outdoor environments, or obtained directly from RGB-D cameras in indoor areas. However, even if a high-end LiDAR is employed, the obtained depth maps are still very sparse and noisy, especially in the regions near the object boundaries, which makes the depth completion task a challenging problem. To address this issue, a few years ago, conventional image processing-based techniques were employed to fill the holes and remove the noise from the relatively dense depth maps obtained by RGB-D cameras, while deep learning-based methods have recently become increasingly popular and inspiring results have been achieved, especially for the challenging situation of LiDAR-image-based depth completion. This article systematically reviews and summarizes the works related to the topic of depth completion in terms of input modalities, data fusion strategies, loss functions, and experimental settings, especially for the key techniques proposed in deep learning-based multiple input methods. On this basis, we conclude by presenting the current status of depth completion and discussing several prospects for its future research directions.

Human leucocytes processed by fast-rate inertial microfluidics retain conventional functional characteristics.

The manufacturing of clinical cellular therapies is a complex process frequently requiring manipulation of cells, exchange of buffers and volume reduction. Current manufacturing processes rely on either low throughput open centrifugation-based devices, or expensive closed-process alternatives. Inertial focusing (IF) microfluidic devices offer the potential for high-throughput, inexpensive equipment which can be integrated into a closed system, but to date no IF devices have been approved for use in cell therapy manufacturing, and there is limited evidence for the effects that IF processing has on human cells. The IF device described in this study was designed to simultaneously separate leucocytes, perform buffer exchange and provide a volume reduction to the cell suspension, using high flow rates with high Reynolds numbers. The performance and effects of the IF device were characterized using peripheral blood mononuclear cells and isolated monocytes. Post-processing cell effects were investigated using multi-parameter flow cytometry to track cell viability, functional changes and fate. The IF device was highly efficient at separating CD14+ monocytes (approx. 97% to one outlet, approx. 60% buffer exchange, 15 ml min-1) and leucocyte processing was well tolerated with no significant differences in downstream viability, immunophenotype or metabolic activity when compared with leucocytes processed with conventional processing techniques. This detailed approach provides robust evidence that IF devices could offer significant benefits to clinical cell therapy manufacture.

Endoscopic Removal of Gastric Foreign Bodies with a Bottle Liner in 12 Dogs (2020-2023).

Endoscopy is widely used to remove gastric foreign bodies using grasping forceps and loop snares to manipulate and retrieve the foreign material. However, as not all foreign bodies can be removed using conventional endoscopic techniques, this case series describes the use of bottle liners for the removal of gastric foreign bodies in 12 dogs between 2020 and 2023. A 4 oz bottle liner (Drop-Ins) was placed at the end of the endoscope and pushed into the stomach. With the help of forceps introduced into the operating channel, the foreign body was pushed into the bottle liner. The bottle liner containing the foreign body was then extracted with the help of traction threads. The technique was used as the initial retrieval method in 5 dogs because of smooth (i.e., difficult to grasp) or sharp (i.e., that may damage the digestive tract mucosa during removal) foreign bodies and as a rescue procedure in 7 dogs. Foreign body retrieval was successful in all 12 dogs, with minor complications reported in 5 dogs (erosions and bleeding of the gastroesophageal sphincter). The use of a bottle liner represents an affordable alternative to gastrotomy when foreign bodies cannot be grasped with forceps or snares.

MTPA Control for DC-Biased Hybrid Excitation Machine Using MTPA Control Law and Virtual Signal Injection

This paper proposes an overall maximum torque per ampere (MTPA) control for dc-biased hybrid excitation machine (dc-biased HEM) using MTPA control law and virtual signal injection. The mathematical model of the machine is first analyzed in synchronous rotating reference frame. According to the characteristic of the mathematical model, a control strategy is proposed and consists of two parts, i.e., an MTPA control law and a virtual dc-biased signal injection. The MTPA control law is employed to calculate the dominant current references while ensuring the rapid dynamic performance. The virtual dc-biased signal injection method is a correction scheme for MTPA current deviation caused by parameter variations. Unlike conventional signal injection techniques, this signal injection method considers the nonlinearity of inductance and does not involve any filters. Thus, it can extract MTPA criterion more accurately and easily. In general, simulation and experimental results validate that the control strategy combined with MTPA control law and virtual signal injection can achieve accurate MTPA operation and rapid dynamic magnetization capability for the dc-biased HEM in real time.

Approach towards surveillance-based diagnosis of acute respiratory illness in India: Expert recommendations

BackgroundEmerging infectious diseases, often zoonotic, demand a collaborative “One-Health” surveillance approach due to human activities. The need for standardized diagnostic and surveillance algorithms is emphasized to address the difficulty in clinical differentiation and curb antimicrobial resistance. ObjectiveThe present recommendations are comprehensive diagnostic and surveillance algorithm for ARIs, developed by the Indian Council of Medical Research (ICMR), which aims to enhance early detection and treatment with improved surveillance. This algorithm shall be serving as a blueprint for respiratory infections landscape in the country and early detection of surge of respiratory infections in the country. ContentThe ICMR has risen up to the threat of emerging and re-emerging infections. Here, we seek to recommend a structured approach for diagnosing respiratory illnesses. The recommendations emphasize the significance of prioritizing respiratory pathogens based on factors such as the frequency of occurrence (seasonal or geographical), disease severity, ease of diagnosis and public health importance. The proposed surveillance-based diagnostic algorithm for ARI relies on a combination of gold-standard conventional methods, innovative serological and molecular techniques, as well as radiological approaches, which collectively contribute to the detection of various causative agents.The diagnostic part of the integrated algorithm can be dealt at the local microbiology laboratory of the healthcare facility with the few positive and negative specimens shipped to linked viral disease research laboratories (VRDLs) and other ICMR designated laboratories for genome characterisation, cluster identification and identification of novel agents.

Approaching code-compliant Non-Destructive Testing of carbon steel weld using Total Focusing Method technique

The Total Focusing Method (TFM) technique is an advanced Non-Destructive Testing (NDT) Ultrasonic Testing (UT) technique. It is usually used together with special acquisition configurations such as Full Matrix Capture (FMC) or Plane Wave Imaging (PWI) and can supply synthetic post-processing results based on a quantity of ultrasonic signals. It is believed that it will accelerate the UT technique revolution toward the artificial intelligence era. Compared to the conventional UT technique, or even advanced UT techniques, such like Time of Flight Diffraction (TOFD) and Phased Array (PA) techniques, this advanced UT technique is well known for its easy-to-interpret and high-resolution representative images. For these reasons, it is used more and more in the flaw sizing and characterization assessment. Following the publication of the standard ISO 23864, TFM technique become a member among all standardized weld inspection techniques. This article presents some related study results toward a code-compliant weld inspection regarding the related standards, dealing especially with the sensitivity calibration which is a key point for the applicability of amplitude-based acceptance criteria.

Combining range-general and range-specific techniques for late-time focused image reconstructiona).

Synthetic aperture sonar (SAS) is an acoustic method for detecting objects in an environment. Conventional SAS image reconstruction techniques invert a forward model based on geometric scattering and straight-line propagation. Acoustic features that do not fit this model, such as multiple scattering and late-time returns, appear out of focus. This paper describes an image reconstruction technique that selectively applies range-general and range-specific methods to improve the focus of late-time returns while maintaining image quality away from the focal plane. The technique is demonstrated on experimental data and compared with a range-specific algorithm.

Broadband Love Wave Phase Velocity Maps Based on Modified Double‐Beamforming of Ambient Noise Cross‐Correlations

AbstractAmbient noise tomography has become a popular method in the past two decades to image the crust and uppermost mantle structure. To date, broadband Rayleigh wave signals can be obtained from ambient noise, which can be utilized to study the earth's interior structure from the surface down to ∼200–300 km depths. However, it is hard to extract intermediate‐ and long‐period (&gt;50 s) Love wave signals from ambient noise using conventional data processing techniques for ambient noise. Array‐based data processing techniques can enhance weak signals. In this study, we adopt a modified algorithm of the double‐beamforming method to extract broadband Love wave signals from ambient noise. We validate the accuracy of the dispersion curves measured from our method by comparing them to those measured from the conventional method. Then, we use a finite frequency ambient noise tomography method to construct broadband Love wave phase velocity maps across the contiguous USA. These phase velocity maps are consistent with those obtained from conventional methods at short periods (&lt;40 s). Finally, we analyze the resolution of our double‐beamforming method based on checkerboard tests and find that the resolution of phase velocity maps based on our method is close to the aperture of the subarrays used in our double‐beamforming method.

ETVO: Effectively Measuring Tactile Internet With Experimental Validation

The next frontier in communications is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">teleoperation</i> – manipulation and control of remote environments with haptic feedback. Compared to conventional networked applications, teleoperation poses widely different requirements, ultra-low latency (ULL) is primary. Realizing ULL communication demands significant redesign of conventional networking techniques, and the network infrastructure envisioned for achieving this is termed as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Tactile Internet</i> (TI). The design of meaningful performance metrics is crucial for seamless TI communication. However, existing performance metrics fall severely short of comprehensively characterizing TI performance due to their inability to capture how well sensed signals are reproduced. We take Dynamic Time Warping(DTW) as the basis of our work and identify necessary changes for characterizing TI performance. Through substantial refinements to DTW, we design <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Effective Time- and Value-Offset (ETVO)</i> – a new method for measuring the fine-grained performance of TI systems. Through an in-depth objective analysis, we demonstrate the improvements of ETVO over DTW. Through subjective experiments, we demonstrate that existing QoS and QoE methods fall short of estimating the TI session performance accurately. Using subjective experiments, we demonstrate the behavior of the proposed metrics, their ability to match theoretically derived performance, and finally, their ability to reflect user satisfaction in a practical setting.

An improved low‐carbon intelligent agriculture system with energy optimization principles using wireless IoT environment

AbstractA low‐carbon agricultural plan and intelligent agriculture control system are designed and completed with a green economy to foster the significant expansion of green resources and environmental assets. This research employs a fixed‐effect panel model to examine the farming cumulative energy savings in 11 cities and regions along the Yamuna Tributary Commercial Region, focusing on both static and dynamic factors. The directional linear equation and the Malmquist–Luenberger (ML) indicator are the key analytical tools. Unlike conventional techniques, regression analysis using cross‐sectional data is the primary tributary. Research has found that a 5.9% decrease in the literacy rate of the working force had a large impact on farming energy efficiency and that for each 1% rise in crop losses, farm energy efficiency would decrease by 0.487%. In addition to mitigating the detrimental effects of industrial design and mechanization on agricultural output, this effort aids in the advancement of smart city design. This activity paves the way for cutting‐edge technology by encouraging people to move to cities, educating the workforce, and giving money to the agricultural sector. The ability of proposed model gives the smart agriculture system with intelligent control principles and energy optimization principles in the deployed wireless‐IoT platform. On this research problem, this paper contributes to new knowledge by approaching agricultural energy efficiency from a green economy perspective, conducting regression analyses of panel data on the most important influencing factors using the advanced statistical analysis tool Eviews, and then drawing the conclusion from the evaluation of metrics that affect farming energy efficiency in our nation. Enhancing productivity while also fostering long‐term growth in the agricultural ecosystem is crucial. It contributes for smart and green technologies adaptation in agriculture filed.