Precise Sensor Research Articles

Smart Voice Controlled Wheelchair for Physically Disabled People

Abstract: In this groundbreaking study, we introduce a state-of-the-art, user-friendly smart voice-controlled wheelchair designed specifically for individuals with physical disabilities. Leveraging advanced technologies, including the powerful Arduino Uno microcontroller, precise ultrasonic sensors for obstacle detection, and seamless Bluetooth connectivity, our wheelchair system redefines the paradigm of mobility solutions. An intuitive mobile application, available for download on popular platforms such as the Play Store, complements the hardware, enabling effortless control and customization through natural voice commands. This paper meticulously details the design, implementation, and evaluation of our smart voice-controlled wheelchair, emphasizing its innovative features and discussing compelling avenues for future improvements.

Creation of Boron Vacancies in Hexagonal Boron Nitride Exfoliated from Bulk Crystals for Quantum Sensing.

Boron vacancies (VB-) in hexagonal boron -nitride (hBN) have sparked great interest in recent years due to their optical and spin properties. Since hBN can be readily integrated into devices where it interfaces a huge variety of other 2D materials, boron vacancies may serve as a precise sensor which can be deployed at very close proximity to many important materials systems. Boron vacancy defects may be produced by a number of existing methods, the use of which may depend on the final application. Any method should reproducibly generate defects with controlled density and desired pattern. To date, however, detailed studies of such methods are missing. In this paper, we study various techniques for the preparation of hBN flakes from bulk crystals and relevant postprocessing treatments, namely, focused ion beam (FIB) implantation, for creation of VB-s as a function of flake thickness and defect concentrations. We find that flake thickness plays an important role when optimizing implantation parameters, while careful sample cleaning proved important to achieve consistent results.

Rapid assessment of degraded frying oil quality using interdigitated microelectrode capacitive sensors

AbstractFrying oil is essential in food processing, influencing both the taste and safety of fried foods. However, its quality can deteriorate with repeated use, posing potential risks. Many current methods for evaluating its quality, such as spectroscopic techniques, are time‐consuming and costly. Our study introduces an affordable and rapid device that uses electrical capacitance to assess the quality of frying oil. We developed a capacitive sensor equipped with interdigitated microelectrodes (IEMs) to measure the oil's dielectric constant. After calibrating the sensor's features, we achieved highly precise results. Our design utilized Corel software for drafting and CNC machinery for precise sensor fabrication. In air, the sensor's measurements closely aligned with theoretical predictions, registering an R2 value above 0.7. We identified a correlation between frying frequency and significant shifts in the dielectric constant across three oil samples. Using a signal circuit to adjust the oscillation frequency and a microprocessor for data interpretation, we classified oils into three safety categories: safe, moderate, and risky. Our device provides a cost‐effective and user‐friendly solution to assess frying oil quality, proactively addressing health concerns arising from oil degradation.Practical Applications: Our capacitive sensor device can be widely applied in the food industry and restaurants, ensuring the safety and quality of fried products. By using this device, manufacturers and kitchens can make informed decisions about reusing frying oil or replacing it as needed, reducing wasted oil. This cost‐saving device also has the potential to contribute to improving food safety issues.

Apparent nonlinear damping triggered by quantum fluctuations

Nonlinear damping, the change in damping rate with the amplitude of oscillations plays an important role in many electrical, mechanical and even biological oscillators. In novel technologies such as carbon nanotubes, graphene membranes or superconducting resonators, the origin of nonlinear damping is sometimes unclear. This presents a problem, as the damping rate is a key figure of merit in the application of these systems to extremely precise sensors or quantum computers. Through measurements of a superconducting resonator, we show that from the interplay of quantum fluctuations and the nonlinearity of a Josephson junction emerges a power-dependence in the resonator response which closely resembles nonlinear damping. The phenomenon can be understood and visualized through the flow of quasi-probability in phase space where it reveals itself as dephasing. Crucially, the effect is not restricted to superconducting circuits: we expect that quantum fluctuations or other sources of noise give rise to apparent nonlinear damping in systems with a similar conservative nonlinearity, such as nano-mechanical oscillators or even macroscopic systems.

Silicon-tapered waveguide for mode conversion in metal-insulator-metal waveguide-based plasmonic sensor for refractive index sensing.

In this study, we have undertaken a comprehensive numerical investigation of a refractive index sensor designed around a metal-insulator-metal (MIM) plasmonic waveguide. Our approach utilizes the finite element method to thoroughly analyze the sensor's performance. The sensor's configuration utilizes a ring resonator design, which has been slightly modified at the coupling segment. This modification enhances the efficiency of light coupling between a bus waveguide and the ring resonator, particularly at the resonance wavelength. This strategic adjustment significantly improves the device's extinction ratio, a critical factor in its functionality. Remarkably, the sensitivity of this sensor is determined to be approximately 1155.71nm/RIU, while it possesses a figure of merit of 25.9. Furthermore, our study delves into the intricate mechanism governing the injection of light into the nanoscale MIM waveguide. We achieve this through the incorporation of silicon-tapered waveguides, which play a pivotal role in facilitating the transformation of a dielectric mode into a plasmonic mode, and vice versa. Ultimately, the findings of this research hold significant promise for advancing the field of plasmonic sensing systems based on MIM waveguide technology. The insights gained here pave the way for the practical realization and optimization of highly efficient and precise plasmonic sensors.

Minimum Detection Concentration of Hydrogen in Air Depending on Substrate Type and Design of the 3ω Sensor.

Hydrogen has emerged as a promising carbon-neutral fuel source, spurring research and development efforts to facilitate its widespread adoption. However, the safe handling of hydrogen requires precise leak detection sensors due to its low activation energy and explosive potential. Various detection methods exist, with thermal conductivity measurement being a prominent technique for quantifying hydrogen concentrations. However, challenges remain in achieving high measurement sensitivity at low hydrogen concentrations below 1% for thermal-conductivity-based hydrogen sensors. Recent research explores the 3ω method's application for measuring hydrogen concentrations in ambient air, offering high spatial and temporal resolutions. This study aims to enhance hydrogen leak detection sensitivity using the 3ω method by conducting thermal analyses on sensor design variables. Factors including substrate material, type, and sensor geometry significantly impact the measurement sensitivity. Comparative evaluations consider the minimum detectable hydrogen concentration while accounting for the uncertainty of the 3ω signal. The proposed suspended-type 3ω sensor is capable of detecting hydrogen leaks in ambient air and provides real-time measurements that are ideal for monitoring hydrogen diffusion. This research serves to bridge the gap between precision and real-time monitoring of hydrogen leak detection, promising significant advancements in the related safety applications.

Measuring highly accurate foot position and angle trajectories with foot-mounted IMUs in clinical practice

BackgroundGait analysis using foot-mounted IMUs is a promising method to acquire gait parameters outside of laboratory settings and in everyday clinical practice. However, the need for precise sensor attachment or calibration, the requirement of environments with a homogeneous magnetic field, and the limited applicability to pathological gait patterns still pose challenges. Furthermore, in previously published work, the measurement accuracy of such systems is often only validated for specific points in time or in a single plane. Research questionThis study investigates the measurement accuracy of a gait analysis method based on foot-mounted IMUs in the acquisition of the foot motion, i.e., position and angle trajectories of the foot in the sagittal, frontal, and transversal plane over the entire gait cycle. ResultsA comparison of the proposed method with an optical motion capture system showed an average RMSE of 0.67° for pitch, 0.63° for roll and 1.17° for yaw. For position trajectories, an average RMSE of 0.51 cm for vertical lift and 0.34 cm for lateral shift was found. The measurement error of the IMU-based method is found to be much smaller than the deviations caused by the shoes. SignificanceThe proposed method is found to be sufficiently accurate for clinical practice. It does not require precise mounting, special calibration movements, or magnetometer data, and shows no difference in measurement accuracy between normal and pathological gait. Therefore, it provides an easy-to-use alternative to optical motion capture and facilitates gait analysis independent of laboratory settings.

Investigation on Sb-doped SnO2 as an efficient sensor for the detection of formaldehyde

The applicability of antimony-doped tin dioxide (Sb-doped SnO2) as a very precise sensor for detecting formaldehyde (HCHO) gas is investigated in this study. The sol-gel method was used to prepare pure SnO2 and Sb-doped SnO2 nanostructures, which resulted in better structural and morphological properties. The prepared samples were analyzed using several characterization techniques, including X-ray diffractometer (XRD), field emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FTIR), UV-Vis spectroscopy and X-ray photoelectron spectroscopy (XPS). A structural investigation indicated the presence of a tetragonal SnO2 phase with a clear preference for the (110) orientation. Furthermore, the crystallite size reduced as the quantity of Sb doping rose. According to FE-SEM analysis, both the undoped (SnO2) and Sb-doped SnO2 samples had polyhedral structures. FTIR analysis verified the presence of organic functional groups in the prepared powder samples. The optical band gap (Eg) values decreased with an increasing concentration of Sb doping in the SnO2 nanostructures. XPS was used to determine the chemical elements of the prepared powder samples. In the gas sensing study, those based on 8 wt% Sb-doped SnO2 (referred to as ATO-8) outperformed the others. At room temperature, the ATO-8 sample demonstrated stronger sensor response, faster response and recovery durations (98 s/74 s), and linear behavior. These enhancements can be attributable to an increase in adsorbed oxygen species caused by Sb doping, highlighting ATO-8's potential as a substance for detecting HCHO. This study emphasizes the potential of ATO-8 as a significant resource for practical use in the detection of HCHO, with benefits such as improved indoor air quality, increased industrial safety, and advancements in environmental monitoring.

Role of losses and coupling in bright-dark metasurfaces mimicking non-Hermitian parity-time symmetric systems

All real systems are essentially non-conservative in nature, which is non-Hermitian in the fundamental premises of the quantum realm. Such open systems obeying parity-time (PT) symmetry can offer intriguing physics, which has sparked much attention in recent years. The thoughtful interplay of loss and gain in PT-symmetric systems can tune the eigenstates from real to complex space passing through a singular point known as an exceptional point (EP) with concurrently coalescing the discrete eigenstates. In this regard, artificially engineered near-field coupled metasurfaces provide a remarkable podium to introduce as well as control loss and coupling strength simultaneously, manifesting a practical channel to attain EP. Motivated by this notion, we have theoretically explored near-field coupled dark-bright-mode assisted terahertz metasurfaces imitating a typical non-Hermitian PT-symmetric system. Structurally, such metasurfaces are realized by utilizing a pair of orthogonally twisted near-field coupled split-ring resonators (bright-dark-resonators). We have meticulously examined such a system with two distinctive approaches, i.e., the loss parameter and inter-resonator coupling strength. Eventually, our exploration demonstrates that judicious modulation of the loss parameter can invoke an undemanding route to approach the other wisely elusive exceptional point. We believe that this comprehensive study of non-Hermitian quantum systems in a photonic context can lead to the development of accurate and precise ultra-sensitive sensors besides other futuristic photonic devices.

Eco-innovation and agricultural sustainability: empirical evidence from South Africa’s agricultural sector

ABSTRACT This study explores the role of eco-innovation in promoting environmental sustainability in the agricultural sector in South Africa. The study applies a mixed-methods approach using both qualitative and quantitative data on eco-innovations. The study is guided by the Resource-Based View (RBV) as a theoretical lens and applies a logistic regression model to explore the relationship between various resources and capabilities and four types of environmental sustainability outcomes. The results suggest that agricultural businesses that invest in developing process innovations, acquire knowledge from external sources, leverage different types of technologies such as precision agriculture and sensor technologies are more likely to achieve improved environmental sustainability outcomes. The study suggests a few policy recommendations that emphasize the importance of creating incentives for agricultural businesses to invest in innovative and sustainable agricultural practices, collaborate with higher education and government research institutions and facilitate adoption of advanced ICTs to promote eco-innovation.

Displacement Calibration of Optical Tweezers With Gravitational Acceleration

In recent years, levitated particles of optical traps in vacuum have shown the enormous potential for precision sensor development and new physics exploration. However, the accuracy of the sensor is still hampered by the uncertainty of the calibration factor relating the detected signal to the absolute displacement of the trapped particle. In this paper, we suggest and experimentally demonstrate a novel calibration method for optical tweezers based on free-falling particles in vacuum, where the gravitational acceleration is introduced as an absolute reference. Our work provides a calibration protocol with a great certainty and traceability, which is significant in improving the accuracy of precision sensing based on levitated optomechanical systems.

IoT-interfaced solid-contact ion-selective electrodes for cyber-monitoring of element- specific nutrient information in hydroponics

This study aims to monitor element-specific nutrient information during hydroponic cultivation by IoT-interfaced miniaturized ion sensors. Because of size, cost, and manufacturing advantages, solid-contact ion-selective electrodes (SCISEs) were fabricated as an ion sensor array and interfaced with wireless embedded-systems to construct an IoT nutrient sensor system (IoNSS) for the first time. The entire IoNSS framework was composed of (i) a nutrient solution sampling and sensing module with SCISEs controlled by an Arduino Due® microcontroller, (ii) a Wio Terminal® microcontroller for automated procedure setting, data recording, and wireless transmission, (iii) a private cloud server (a Network Attached Storage equipped with Node-RED® and MongoDB®) for data management, and (iv) MQTT webpage-based interactive interfaces. In experiments, we found that potentiometric signal resolution and noise of the Arduino-interfaced SCISEs were significantly improved and approached to instrumental DAQ-like quality by additional delta-sigma ADC (ADS1115®) chip conditioning. This facilitated cost-effective harvest of precise and high-quality IoT ion sensor data. Before on-site applications, each SCISE was two-point calibrated in multiple-ion solutions and was checked with the fixed interference method. The ion concentration measurements were also compared with those of commercial ISEs and ion chromatography. To test the system’s feasibility, the IoNSS was applied to cyber-monitoring of K+, NO3–, and NH4+ concentrations during two-week hydroponic cultivation of arugula (E. vesicaria) in an indoor plant factory (in Northern Taiwan) with a modified Cornell solution and an outdoor greenhouse (in Southern Taiwan) with a modified Yamasaki solution, respectively. It was demonstrated that the IoNSS was capable of real-time observation of the crop’s nitrate/ammonium utilization and nutrient solution’s EC-element dependency. Besides, the web interfaces successfully reported growing condition-dependent ion signals in a simultaneous and remote manner. To sum up, this work achieves novel cybermonitoring of element-specific nutrients by IoT-interfaced SCISEs and paves a promising way for intelligent hydroponic management.

Quantum sensors making waves across europe

AbstractEurope has witnessed remarkable developments in quantum sensing technology in recent years. Various companies have entered the field from different perspectives and made significant strides in harnessing the power of quantum phenomena to create highly sensitive and precise sensors. These sensors have the potential to revolutionize a wide range of industries, including healthcare, telecommunications, navigation, and more.

Efficient load balancing Adaptive BNBKnapsack Algorithm for Edge computing to improve performance of network

INTRODUCTION: In present days, Automation of everything has become essential. Internet of things (IoT) play an important role among all medical advances of IT. In this paper, feasible solutions are discussed to compare and design better healthcare systems. A thorough investigation and survey of suitable approaches were done to select IoT based systems in hospitals consisting of various high precision sensors. OBJECTIVES: The challenge healthcare system face is to manage the real time patient’s data with high accuracy. Second challenge is at fog devices level to manage the load distribution to all sensors with limited availability of bandwidth. METHODS: This paper summarizes the selection criterions of suitable load balancing algorithms to reduce energy consumption and computational cost of fog devices and increase the network usage that are supposed to be used in IoT based healthcare systems. According to the survey BNBKnapack algorithm has been selected as best suitable approach to analyze the overall performance of fog devices and results are also verify the same. RESULTS: Comparative analysis of Overall performance of fog devices has been proposed with using SJF algorithm and Adaptive BNBKnapsack algorithm. It has been observed by analysing system performance, which is found as best among other load balancing algorithm Adaptive BNBKnapsack is successfully reduce the energy consumption by (99.29%), computational cost by (98.34%) and increase the network usage by (99.95%) of system CONCLUSION: It has been observed by analysing system performance, Adaptive BNBKnapsack Load balancing is successfully able to reduce the computational cost and energy consumption also increase the network usage of the fog network. The performance of the system is found best among other load balancing algorithm.

Enhanced electrochemical detection of nitrobenzene using zinc oxide-carboxylated graphene oxide composite as sensor

This study focused on the electrochemical detection of nitrobenzene (NB) using a glassy carbon electrode (GCE) modified with carboxylated graphene oxide (c-GO) that contained zinc nanoparticles (ZnO@c-GO/GCE). ZnO@c-GO nanocomposite modified GCE structural studies using SEM, XRD, and XPS showed that ZnO nanoparticles were successfully incorporated into c-GO nanosheets. Through the cooperative action of c-GO nanosheets and ZnO nanoparticles, electrochemical studies using electrochemical impedance spectroscopy, cyclic voltammetry, and amperometry demonstrated that the presence of ZnO nanoparticles and c-GO facilitated electron transfer between the redox probe and the electrode surface. Results showed that ZnO@c-GO/GCE had a broad linear sensitivity range of 0.1091 μA/μM, a considerably low limit of detection of 0.013 μM, and a linear range of 100–3000 μM. The prepared real sample of industrial wastewater samples used in the study to determine the precision of the proposed sensor for NB determination revealed significant recovery values (over 94.50 %) and acceptable accuracy (RSD less than 4.21 %), indicating that ZnO@c-GO (2:3)/GCE can be used as a precise NB electrochemical sensor in environmental applications.

Enhanced mechanical properties of giant magnetostrictive Tb-Dy-Fe alloy via constructing semi-coherent interface between matrix phase and ductile grain boundary phase

Giant magnetostrictive Tb-Dy-Fe alloys in the form of thin sheets or fine wires are required in precision micro-actuators and sensors. However, Tb-Dy-Fe alloys are too brittle to undergo machining and application. In the present work, we investigated the effects of diffusing the Dy36Cu64 alloy into the grain boundary phases of the <110>-oriented Tb0.30Dy0.70Fe1.95 alloy to modify the microstructural, mechanical, and magnetostrictive properties. Microstructural analysis revealed the introduction of Cu into the grain boundary phase through the diffusion treatment, transforming the brittle rare earth (RE)-rich grain boundary phase into a ductile (Tb,Dy)Cu grain boundary phase and changing the non-coherent interface to a semi-coherent one between the (Tb,Dy)Fe2 matrix phase and the grain boundary phase without affecting the microstructure of the matrix phase. The as-diffused Tb0.30Dy0.70Fe1.95 alloy exhibited significantly improved mechanical properties, with its tensile strength, bending strength, and fracture toughness at room temperature increasing to 44.6 MPa, 106.8 MPa, and 2.36 MPa m1/2, respectively, which were 2, 2.4, and 1.5 times those of the non-diffused sample. This was attributed to the formation of ductile (Tb,Dy)Cu grain boundary phase and semi-coherent interfaces. Furthermore, the magnetostrictive strain of the as-diffused Tb0.30Dy0.70Fe1.95 alloy reached 1448 ppm, suggesting that there was minimal impact on the magnetostrictive properties, due to the small influence of grain boundary diffusion on the matrix phase.

TNFα induced by DNA-sensing in macrophage compromises retinal pigment epithelial (RPE) barrier function

Increasing evidence suggests that chronic inflammation plays an important role in the pathogenesis of age-related macular degeneration (AMD); however, the precise pathogenic stressors and sensors, and their impact on disease progression remain unclear. Several studies have demonstrated that type I interferon (IFN) response is activated in the retinal pigment epithelium (RPE) of AMD patients. Previously, we demonstrated that human RPE cells can initiate RNA-mediated type I IFN responses through RIG-I, yet are unable to directly sense and respond to DNA. In this study, we utilized a co-culture system combining primary human macrophage and iPS-derived RPE to study how each cell type responds to nucleic acids challenges and their effect on RPE barrier function in a homotypic and heterotypic manner. We find that DNA-induced macrophage activation induces an IFN response in the RPE, and compromises RPE barrier function via tight-junction remodeling. Investigation of the secreted cytokines responsible for RPE dysfunction following DNA-induced macrophages activation indicates that neutralization of macrophage-secreted TNFα, but not IFNβ, is sufficient to rescue RPE morphology and barrier function. Our data reveals a novel mechanism of intercellular communication by which DNA induces RPE dysfunction via macrophage-secreted TNFa, highlighting the complexity and potential pathological relevance of RPE and macrophage interactions.

A 0.9-V 6400-μm2 Resistor-Based Temperature Sensor With a One-Point Trimmed 3σ Inaccuracy of ±0.64 °C from −50°C to 125 °C

This paper describes a compact and precise resistive temperature sensor based on a frequency-locked loop (FLL) intended for thermal monitoring in system-on-chips. The FLL incorporates a switched-capacitor loop filter improving the sensors inaccuracy and FLL outputs are converted into a digital code with an edge-combined counter for efficient frequency-to-digital conversion. A prototype sensor is fabricated in 65-nm CMOS process and occupies only 6,400 μm2. It achieves a one-point trimmed 3σ inaccuracy of 10.64 ∘C over a wide temperature range of.50 to 125 ∘C. Operating at 0.9 V supply, it consumes 40 μW and achieves 2.2 mK resolution in a 1-ms conversion time, which corresponds to a resolution FoM of 0.19 pJ7K2.

Development of Electrochemical Sensor Using Iron (III) Phthalocyanine/Gold Nanoparticle/Graphene Hybrid Film for Highly Selective Determination of Nicotine in Human Salivary Samples.

Nicotine is the one of the major addictive substances; the overdose of nicotine (NIC) consumption causes increasing heart rate, blood pressure, stroke, lung cancer, and respiratory illnesses. In this study, we have developed a precise and sensitive electrochemical sensor for nicotine detection in saliva samples. It was built on a glassy carbon electrode (GCE) modified with graphene (Gr), iron (III) phthalocyanine-4,4',4″,4'''-tetrasulfonic acid (Fe(III)Pc), and gold nanoparticles (AuNPs/Fe(III)Pc/Gr/GCE). The AuNPs/Fe(III)Pc/Gr nanocomposite was prepared and characterized by using FE-SEM, EDX, and E-mapping techniques to confirm the composite formation as well as the even distribution of elements. Furthermore, the newly prepared AuNPs/Fe(III)Pc/Gr/GCE-nanocomposite-based sensor was used to detect the nicotine in phosphate-buffered solution (0.1 M PBS, pH 7.4). The AuNPs/Fe(III)Pc/Gr/GCE-based sensor offered a linear response against NIC from 0.5 to 27 µM with a limit of detection (LOD) of 17 nM using the amperometry (i-t curve) technique. This electrochemical sensor demonstrated astounding selectivity and sensitivity during NIC detection in the presence of common interfering molecules in 0.1 M PBS. Moreover, the effect of pH on NIC electro-oxidation was studied, which indicated that PBS with pH 7.4 was the best medium for NIC determination. Finally, the AuNPs/Fe(III)Pc/Gr/GCE sensor was used to accurately determine NIC concentration in human saliva samples, and the recovery percentages were also calculated.

Exploring the bacterial genetic diversity and community structure of crude oil contaminated soils using microbiomics

The impact of environmental pollution in air and water is reflected mainly in the soil ecosystem as it impairs soil functions. Also, since the soil is the habitat for billions of organisms, the biodiversity is in turn altered. Microbes are precise sensors of ecological contamination, and bacteria have a key and important function in terms of bioremediation of the contaminated soil. Hence in the current work, we aimed at assessing the unidentified bacterial population through Illumina MiSeq sequencing technology and their community structural changes in different levels of petroleum-contaminated soil and sludge samples (aged, sludge, and leakage soil) to identify unique bacteria for their potential application in remediation. The studies showed that major bacterial consortiums namely, Proteobacteria (57%), Alphaproteobacteria (31%), and Moraxellaceae (23%) were present in aged soil, whereas Proteobacteria (52%), Alphaproteobacteria (33%), and Rhodobacteraceae (28%) were dominantly found in sludge soil. In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. In addition, we also analyzed various physicochemical properties of soil including pH, temperature, salinity, electrical conductivity, alkalinity, total carbon, total organic matter, nitrogen, phosphorus and potassium to calculate the soil quality index (SQI). The SQI of aged, sludge and leakage soil samples were 0.73, 0.64, and 0.89, respectively. These findings show the presence of unexplored bacterial species which could be applied for hydrocarbon remediation and further they can be exploited for the same.