This PDF file contains the front matter associated with SPIE Proceedings Volume 13276, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

In this paper, we are detecting adulteration in olive oil using an optical fiber probe-based near-infrared (NIR) spectroscopy technique. Based on the market price, palm olein oil is identified as a low-cost adulterant for olive oil. Samples with different volume percentages of palm oil in olive oil are prepared and tested. The NIR spectrum of the samples clearly shows a decrease in reflectivity with an increase in adulterant concentration in olive oil. The sensitivity obtained in the region of 0-25% adulteration is a 0.6% decrease in reflectivity per 1% adulteration. Based on the results, a low-cost setup for detecting adulteration of olive oil with palm oil is also proposed.

This paper presents a highly sensitive, robust, fully packaged accelerometer utilizing Fiber Bragg Grating (FBG) technology, engineered to offer exceptional performance in dynamic environments. The proposed accelerometer integrates self-temperature compensation mechanisms to ensure accurate readings across varying thermal conditions. Leveraging FBG technology, the device achieves a remarkable sensitivity of 1000 pm/g and a resonant frequency of 184 Hz, facilitating efficient detection of rapid changes in acceleration. The design incorporates two Fiber Bragg gratings as sensing elements and innovative structural configurations to enhance robustness and reliability in harsh operating environments. The design is optimised for required parameters using extensive modelling and simulations. Furthermore, the extraction of velocity is carried out through efficient signal processing algorithm which makes it easy to operate and field deployable. In this research work, experimental validation along with a commercial accelerometer demonstrates the efficacy of the proposed accelerometer, showcasing its potential for applications where high sensitivity and resilience to temperature fluctuations are paramount. Moreover, the developed accelerometer is experimented for ground vibrations and is found to be operative up to a range of 12 m. This research contributes to the advancement of sensor technology, offering a promising solution for demanding acceleration measurement requirements in various engineering disciplines. In future, the developed accelerometer will be employed for real time measurement of blast induced vibrations in mining applications.

Tilt sensors are devices that measure the tilt or slope of an object with respect to a reference. Fibre Bragg Grating (FBG) tilt sensors are a specific type of tilt sensor that utilizes the principle of Bragg’s law in fiber optics to measure tilt angles. In a FBG tilt sensor, the optical fibre is usually placed such that there is a shift in the Bragg wavelength with the change of orientation of the monitored object thus eliciting a sensor response. The advantages of an FBG tilt sensor over traditional sensor is its high precision of measurement and insensitivity to EMI. The FBG tilt sensor in this study is designed to operate accurately and reliably in the presence of vibrations or mechanical oscillations over a range of 0-50°. The structure of the sensor consists of the sensing element attached to a single body cantilever with optimized variable cross-section for adequate strain enhancement. The sensitivity of the sensor is approximately 31 pm/° and the resonant frequency is approximately 40 Hz. A vibration isolation mechanism is designed for this sensor where a neoprene pad is attached between the main body and the mount of the sensor. A finite element analysis is conducted to comparatively verify the sensor’s performance with and without the vibration isolation scheme. It has been found from the results that the current design scheme has been effective in isolating the response of the sensor from environmental vibrations. This sensor can thus be reliably used in machines/structures subjected to random vibrations in various application areas such as aerospace, automotive, structural health monitoring, and industrial automation, where stable and accurate measurements are crucial.

In this work, Chalcogenide coaxial fiber has been studied with step refractive indices in the inner and outer cores for dispersion compensation in the region of wavelength from 1.46 μm to 1.62 μm employing simple coupled mode analysis for the first time according to our knowledge. In designing the coaxial fiber structure, we have considered three ▵₁ values for a fixed ▵₂ value where ▵₁ and ▵₂ are respectively large and small relative refractive index differences. The effects of change in ▵₁ on the effective refractive indices, phase matching wavelengths (PMWs), and the dispersion coefficients with variation of wavelength of the coaxial fiber have been studied and reported in this paper. The maximum value of negative dispersion coefficients -1627 ps/nm-km, -1542 ps/nm-km and -1455 ps/nm-km are found at PMWs 1.511 μm, 1.550 μm, and 1.586 μm respectively. The choice of different ▵₁ is enabling the maximum negative dispersion peak and the PMW to be tuned inside the wavelength window of optical communication. The proposed coaxial fiber will exhibit much importance in the field of optics and photonics.

In this paper, we have estimated splice-loss due to splicing of liquid-filled photonic crystal fiber (LFPCF) with single mode step index fiber using our full-vectorial finite difference method at wavelength 1.55 μm with change in various fiber parameters. We tailored the LFPCF parameters to achieve the minimum splice loss and found very minimum loss at the pitch size ranging from 2.0 μm to 4.0 μm at the relative air hole size (d/Ʌ) 0.45. Further, we have elucidated the splice loss due to the transverse offset. In this analysis, it is seen that the loss is increasing gradually when the transverse offset value increases. In our investigation, we considered the LFPCF having the first ring filled with liquid of 20% water-glycerin solution. Our computation technique to calculate various propagation characteristics including splice loss of LFPCF with or without any transverse offset will have significant contribution to the system designers.

We study generation and spreading of light at the most fundamental level within the classical theory. We model the light emitter as a sinusoidally oscillating point-charge. We use “PyCharge” for computing the electric and magnetic fields associated with such an emitter. Fields are plotted for two physically distinct processes, both regarded as occuring in a single frame F1: Process 1 has a fixed emitter, and Process 2 has a moving emitter. The wave-fronts of the emitted light are found to be circular in shape for both the processes; it’s not elliptical for Process 2. We then construct a second frame, F2, that moves with the same velocity as the uniform motion of the emitter in Process 2. We calculate the fields of Process 2, but using the calculational procedure of P1 in frame F2. Thus, we use the Lorentz transformations and the procedure for a fixed emitter in order to calculate the fields due to a moving emitter. The fields thus computed show results that are numerically identical to those for Process 2 in F1, albeit at a non-negligible computational cost. Interspersed also are some novel observations and remarks concerning Maxwell’s vs. Lorentz’ aether, the Lorentz transformations, and the Special Theory of Relativity. All in all, this paper aims to provide that basic layer of results on the top of which our work towards extending the conceptual and mathematical schema used in the relativity principles, will be offered in future.

In this work, we propose and analyse the performance of a cascaded long period grating (LPG) coupled with an embedded-core Fiber-based Mach-Zehnder interferometer (MZI) for sensing applications. We investigate the improved sensing capabilities made possible by this hybridized setup through experimental. By adding further phase shifts to the interferometric output, the cascaded LPGs allow for the accurate detection of environmental variables like temperature and refractive index. We optimize for optimal sensitivity and accuracy by methodically analysing the parameters on the sensor performance. However, by employing cascaded LPFGs instead of a single LPFG, we overcome this limitation and unlock new potential for sensing applications. According to our experimental work, the suggested MZI-LPG sensor platform has a lot of potential for sensing. This might lead to improvements in industries.

Optogenetics provides the sub ms neuronal activity and with single neuron control and sub ms precision this technique already proved its potential for various medical applications. Optically control neuromorphic computing is important on the parameters of Scalability, energy efficiency and frequency of information processing. Optogenetic Switching provides neuronal inhibition, activation, bi-stable, bi-directional and two-photon optical control of neuronal signaling individually and also in a network. In this Paper, we are presenting the single spike and neuronal firing study of optogenetic switching. Here vf-Chrimson expressing Interneuron model has been used to study the irradiance effect on neuronal spike. By the single spiking on/off switching has been used to design the two input simple logic gates by setting threshold irradiance at 1.2 mW/mm². Optogenetic based computing circuits are able to provide better scalability, tunability and temperature stability.

Yttrium is the most common product of nuclear fission in Uranium. The isotopes of Yttrium can be used in radiotherapeutics. The other compounds of yttrium have different Applications. Among all these compounds, YIG (Yttrium Iron Granet), also known as Y₃Fe₅O₁₂, a synthetic garnet having different magnetic properties compared to other compounds. In YIG, the iron ions exhibit different spins in two coordination sites, resulting in their magnetic behaviour. It has various Acoustic, magneto-optical and microwave applications. This paper uses wavelength Dispersive X-ray fluorescence (WDXRF) to find its energy when compared to theoretical energies, Energy shifts in the compound, intensity ratios and its relatives.

The kinetic analyses of many-particle soft matter often employ many simulation studies of various physical phenomena which supplement the experimental limitations or compliment the theoretical findings of the study. Such simulations are generally conducted by the numerical integration techniques of the governing equations. In the typical case of collisionless electrostatic systems such as electrostatic plasmas, the Vlasov-Poisson (VP) equation system governs the dynamical evolution of the particle phase-space. The one-dimensional position-velocity (1D-1V) particle phase-space, on the other hand, is known to exhibit direct analogy with ordinary two-dimensional fluids, wherein the Vlasov equation resembles the fluid continuity equation of an in-compressible fluid. On the basis of this fluid-analogy, we present, in this work, a new numerical integration scheme which treats the 1D-1V phase-space as a two-dimensional fluid vector space. We then perform and present analyses of numerical accuracy of this scheme and compare its speed and accuracy with the well-known finite splitting scheme, which is a standardised technique for the numerical Vlasov-Poisson integration. Finally, we show some simulation results of the 1D collisionless electrostatic plasma which highlight the higher speed and accuracy of the new scheme. This work presents a fast and sufficiently accurate numerical integration technique of the VP system which can be directly employed in various simulation studies of many particle systems, including plasmas.

The integration of the storage of optical data using fiber loops and extremely rapid optical based switching via nonlinear optical loop mirrors (NOLMs) are recognized as an optimal approach for all-optical processing. This article presents a novel integration of these technologies to create an efficient buffering-switching device aimed at mitigating signal contention. Through thorough analysis, we explore the limitations of this integrated device in achieving error-free processing across multiple buffering cycles. Various factors, such as different types of noise leading to fluctuations in intensity of buffered and demultiplexed signals, are assessed. Additionally, we delve into the switching characteristics of NOLM demultiplexer to provide a comprehensive understanding of the device's performance.

Legume belongs to the Fabaceae family and is considered poor man's meat. Legume seeds contain high levels of carbohydrates, protein, minerals, vitamins and fibre that are good for health and prevent from getting numerous diseases. Besides having high nutritional value, legume seeds regain the soil structure and improve productivity. The goal of the study is to examine the characteristics of five different legume seeds based on Fourier Transform Infrared spectra, moisture content, fat content, and protein content. The five legume seeds, black chickpea, cowpea, white chickpea, small dry bean and red lentil, were used to predict the presence of fat, protein sand moisture using different methods. The protein content for the sample varied from 10.74% to 15.58%, fat from 2.42% to 8.2%, and moisture from 10.38% to 13.22%. In samples like white chickpeas, small red beans, and cowpeas, protein content was similar but found less in black chickpeas and more in red lentils. The fat content was higher in black chickpeas and low in red lentils, whereas the moisture content was almost the same for all samples.

Electronic component cooling is achieved mainly through the provision of fin arrays as heat sinks located on the processing components. This paper aims to present a methodology to relate convection current characteristics obtained from Schlieren imaging with heat transfer characteristics for fin arrays. For this experiment, fin arrays were fabricated for various fin heights, fin spacings, fin widths and convection current footage for all these configurations was recorded. The velocity values obtained from the Schlieren footage was compared with computational fluid dynamics (CFD) simulations of the fin arrays and were found to be consistent. The plume velocity is related with parameters like surface temperature and average heat transfer rate. It is observed that increasing fin height (h) increases heat transfer rate and plume velocity, up to 12mm beyond which fin array choking causes a decrease. Varying the fin spacing (s) keeping fin width (t) constant yields an optimum output at 5 fins and this trend can also be explained by fin choking effects. Varying the number of fins, and fin width, with a constant spacing cause comparatively small changes in heat transfer rates and plume velocity, suggesting that fin spacing is more significant of a factor than fin thickness.

This research examined the optimum requirements for revamping virtual topology for wavelength-routed networks under dynamic traffic demand for mesh physical topology networks. We analysed the optimization of congestion and entire output using the Yen’s K-shortest path algorithm, which is a new approach to investigate the optimum condition for transmission according to time and the number of users. We also consider energy usage during optimal path selection. Previous studies have primarily focused on providing configuration strategies exclusively for selected light paths, with limited consideration for the overall physical topology configuration. Contrarily, the method proposed in this paper can be applied to optimize light path scenarios across various physical topologies.

This study proposes a novel design for a compact and wideband absorber that targets microwaves in C, X, and Ka frequency bands. The design involves imprinting a resistive microwave frequency selective surface (FSS) onto an FR-4 dielectric interlayer integrated with a vacuum spacer. The FSS is comprised of a flower-shaped pattern. In simulation studies, the FR-4 substrate has ~ 0.2 mm thickness, with a 4.3 effective permittivity (εr), and a loss tangent (tanδ) of 0.02, whereas the vacuum spacer has a thickness of ~ 4.2 mm and ε=μ=1. A 0.035 mm-thick copper plate used as a bottom plane to reduce the transmission. The pattern was designed using 150 Ω/sq. resistive ink. Simulation results revealed that the absorber could achieve a -10 dB reflection loss over a frequency range of 5 – 15 GHz and 33.1 - 41.3 GHz. This design is obliquely stable from 0°– 70° and polarization insensitive from 0° – 90°; degrees for both modes of polarisation TE as well as TM. These findings make it suitable for realistic stealth applications.

The realization of object invisibility in the microwave region is of great tactical importance. Herein, we report on designing and simulating a carpet-based cloak composed of a thin dielectric metasurface. Initially, simulations were performed to fix the texture and design of the carpet. For this purpose, a single-frequency TE mode was chosen, and simulations were conducted to investigate reflection at a launched electric power at a varying angle. The dielectric surface has been architected with one order of magnitude mismatch in the design texture. The study revealed that the texture could conceal the object effectively to an extent, thereby not changing the signature of the reflecting field. The power loss analysis was carried out for different launch power on the carpet. Linear, circular, and elliptical excitation modes of plane waves have been studied and observed. Electric field and far-field analysis have been discussed and correlated for the developed carpet geometry. Details have been presented.

The textile industry significantly contributes to toxic wastewater generation, with processing steps consuming large volumes of water and releasing hazardous dyes. These dyes, with complex aromatic structures, are stable and challenging to remove using conventional on-site treatments. Herein, the present work investigates the comparative effectiveness of various techniques for treating textile dye wastewater, including biosorption using agricultural waste, bioremediation using microbial consortia, and photocatalytic degradation. A simulated textile waste has been coated with commercial blue dye and further treated with synthesised nanoparticles of bismuth vanadate (BiVO₄). It shows an effective activity of about 65% dye degradation within 1 hour of treatment. The residual dye has adsorbed in a packed bed reactor (PBR) with different agricultural waste biomass such as rice stalk, peanut hulls, sawdust. The adsorption led to more than 80% removal of textile dyes from the dye solution. The bioremediation process has carried out to degrade the residual dyes eluting from the biomass PBR and the dye recovered by solvent from the biomass adsorbent. It has observed that the dye containing wastewater eluted from the PBR and completely degraded by microbial degradation within 24-72 hours of culture. Based on these findings, we propose a combined approach of nanomaterials enabled photocatalysis and biosorption that leverages the strengths of each method, breakdown of toxicants via photocatalysis coupled with the microbial degradation and biosorption to completely remove toxicants for releasing safe water from textile industry.

Herein, we reported the synthesis and characterization of anthraimidazole based gelation molecule for the detection of toxic anions which are known till date (F^- and CN^-). Gels are further characterized by powdered XRD, FE-SEM, TGA-DSC, FT-IR. The primary force responsible for the gel formation in organic medium is the hydrogen bonding interaction. The SEM image suggested a fibrous like framework for the formation of gel. XRD data provide the π-π interactions for gel formation. The gel was used for selective detection of CN^- ion in aqueous-organic medium. The change in colour and breaking of gel was found for CN^- ion. The probable mechanism for breaking of gel might be due to the deprotonation of -NH- hydrogen and other weak intermolecular forces.

In this work, we show the simple experimental methodology to obtain pure zinc sulphide (ZnS) quantum dots in an aqueous solution. ZnS quantum dots are synthesized by a cost-effective and facile chemical method. The as-prepared quantum dots are observed for different time intervals and have undergone characterisation for their optical, structural and morphological analysis by UV-visible, Photoluminescence, X-ray diffraction, and Scanning Electron Microscopy.

Low-cost and rapid synthesis of bismuth, cobalt modified ZnO-GCN nanocomposite was achieved using facile hydrothermal co-precipitation method and ultra sound assisted hydrothermal method for composite formation. The nanocomposite were characterized by advanced techniques such as SET, TEM, XRD, EDAX, FT-IR, UV-DRS etc., and were investigated for water pollution treatment through photodegradation to eliminate xylenol orange organic dye. Characterization revealed the presence of all the dopants in the synthesized material with high purity and good particle size. The nanoparticles were utilized for the solar degradation of xylenol orange organic dye under eco-friendly solar radiation. The optimal degradation parameters were found to be a catalyst dose of 1.5 g L⁻¹, dye concentration of 10 mg L⁻¹, pH of 8, and 180 minutes of solar radiation. The synthesized nanocomposite was effective for dye degradation.

The research portrayed here is deals with the synthesis of bare Co₃O₄ material and carbon nanotubes modified g-C₃N₄- Co₃O₄ material. Initially, bare cobalt oxide was synthesized by co-precipitation technique. The Co₃O₄ was utilized for preparing CNT-g-C₃N₄-Co₃O₄ nanocomposite material by heat and beat method. These both solid materials viz. Co₃O₄ and CNT-g-C₃N₄-Co₃O₄ were utilized for designing the gas sensor by means of standard screen printing method. Both these fabricated materials were analyzed by several material characterization techniques. From XRD study the structural data of both these materials was fetched. From XRD analysis the cubic lattice of Co₃O₄ was confirmed. The scanning electron microscopy was studied for both these materials to investigate the topographic and surface characteristics. While, the elemental composition was these materials was investigated by EDS analysis. The crystal lattice and nature of the prepared material (amorphous or crystalline) was known from HR-TEM analysis. The amorphous nature of CNT-g-C₃N₄-Co₃O₄ was confirmed from SAED pattern. The BET was investigated for surface area and porosity. The magnetic characteristics of these materials were confirmed by VSM analysis. The photo lithographically fabricated sensor materials were tested for gas sensing study of several toxic, flammable gases CO, NO₂, LPG and petrol vapors. In addition to that the materials were also utilized for humidity assay investigation. The useful gas detection characteristics were investigated thoroughly which includes the response of a sensor, specific selectivity towards tested gases, reusability, and comparison of the sensor, effect of gas concentration and effect of temperature was investigated for both these sensors. From overall investigation it was observed that the g-C₃N₄- Co₃O₄ is excellent sensor towards carbon monoxide and volatile petrol gas at moderate concentration and optimum thermal conditions.

Solar renewable energy is the need today to combat the high decline rate of storage of fossil fuels. Paper presents electronic and optical analysis of KGeBr₃ by employing Density Functional Theory using mBJ potential in FP-LAPW environment using WIEN2K package. Computed energy gap of KGeBr₃ found 0.54 eV in the reciprocal lattice space. Absorption coefficient analysis manifests that KGeBr₃ material absorbs light in the visible spectrum and Si absorbs light in the ultraviolet spectrum. Hence, it is predicted that perovskite KGeBr₃ material will have strong potential to work as a high efficient solar cell in tandem perovskite-Si configuration.

In this work, a green synthesis route of Ag-ZnO (Silver-zinc oxide) nanocomposites was investigated employing aqueous extract of Fraxinus floribunda bark. The synthesized Silver-zinc oxide nanocomposites were studied using techniques such as ATR FTIR, UV- Vis, SEM-EDX, and XRD. Based on the results, the optimal conditions for the synthesis of silver-zinc oxide nanocomposites were an Ag concentration of 8%, 80°C, and a pH of 7-8. The ATR-FTIR tests confirmed the existence of flavonoid, phenols and characteristic bands of Silver and Zinc oxide bands, which work as stabilizing and reducing agents. When Silver-zinc oxide nanocomposites were evaluated for their photocatalytic potential under visible light irradiation using the Methylene Blue (MB) dye, 98 percent photodegradation was observed within 30 minutes for 8% Silver-zinc oxide nanocomposites. The significant photocatalyst for the maximum degradation of MB was shown by 8% Silver-zinc oxide nanocomposites as it showed the higher reaction rate constant compared to other nanocomposites. The antioxidant activity of the nanoparticles was studied against radicals of DPPH (2,2-diphenyl-1-picrylhydrazyl) to assess their ability to capture radical species. The highest percentage scavenging activity of 78% was shown by 8% Ag-ZnO nanocomposite. Ag nanoparticles found on the zinc oxide surface enhances photocatalytic degradation by minimizing the photo-induced recombination charge carriers within the nanocomposites.

In the present work, a scheme is proposed to study the work distribution of dust particle confined in a time dependent harmonic potential in Argon DC glow discharge plasma. Dynamics of dust particle in plasma is a perfect example of stochastic system. The dust particle is brought from initial equilibrium condition to final non-equilibrium condition by varying the stiffness coefficient of the trapping sheath potential and it is studied using the overdamped Langevin equation. The various computation parameters such as mobility, temperature, dust particle response time, magnitude of confining sheath potential, etc are chosen to be in agreement with typical dusty plasma experimental conditions usual created in laboratories. The governing first order stochastic equation is computationally solved using Euler-Maruyama scheme. Parameters such as the mean squared deviation, position probability distribution and work distribution are obtained from the simulation. The non-Gaussian position and work distribution shows the non-equilibrium features of harmonically trapped dust particle in the sheath region of glow discharge plasma. Thus, the present work, demonstrates the capability and promising features of research in the field of non-equilibrium statistical physics of dusty plasma medium.

We have studied the viscoelastic and acoustic properties of binary mixtures of ethanol and gasoline at 300 K at various ethanol concentrations ranging from 10, 28, 46, 64, 82 and 100 percent. Ultrasonic velocity (𝑈), density (ρ) and viscosity (η) of these mixtures were measured by using ultrasonic interferometer, density bottle and Ostwald viscometer at the constant temperature 300 K. From these measured parameters, various viscoelastic and acoustic properties such as adiabatic compressibility (β), acoustic impedance (𝑍), intermolecular free length (𝐿_𝑓), relative association (𝑅_𝐴) and relaxation time (τ) were calculated. It is observed that some properties such as ultrasonic velocity, adiabatic compressibility, acoustic impedance and intermolecular free length exhibit a nonlinear variation with ethanol concentration indicating intermolecular interaction between ethanol and gasoline, while the other properties including density, relative association, viscosity and relaxation time increase steadily and linearly with ethanol concentration. We have attempted to interpret these results by using physicochemical properties of ethanol and gasoline, their intermolecular interaction, miscibility and compatibility. These results lead to a conclusion that ethanol is miscible and compatible with gasoline and it affects the properties of gasoline.

In this work, we study the drag experienced by a probe quark in charged AdS Gauss-Bonnet (GB) gravity with an attached cloud of string. The dissipative force is calculated using gauge/gravity duality with the consideration of the Reissner-Nordstrom AdS Gauss-Bonnet with cloud of string as dual bulk. The drag is studied in terms of the temperature (T), Gauss-Bonnet constant (α), potential Φ and the density of the string cloud (a). The drag experienced by the external quark is found to increase with increase in the corresponding parameters T, α, Φ and a.

In the current era of climate change, variability in rainfall patterns is an important research topic. This is significant in the context of extreme weather events and disasters, as well as in the context of the availability of usable water for communities. The current study presents an investigation into the nonlinear characteristics of rainfall over Kerala, India. The majority of rainfall received over Kerala is during the summer monsoon season (from June to September). However, a good amount of rainfall is obtained during the winter monsoon which is from October to December, as well as during the pre-monsoon season. Here the technique of correlation dimension is utilized to study nonlinear systems exhibiting intricate interdependencies over time. By calculating a value known as correlation dimension, if it is increasing with a parameter called embedding dimension, it would reveal the occurrence of complexity and unpredictability in the rainfall patterns. Otherwise, if correlation dimension stabilizes beyond a certain point, it would suggest that the rainfall dynamics settle into a more stable and potentially predictable pattern. The findings of this analysis revealed that if the embedding dimension increases, the correlation dimension also increases, indicating the existence of complexity and unpredictability in the rainfall pattern.

Monitoring crops is challenging with the help of traditional methods like manual surveys and crop-cutting experiments, which are time-consuming and require efforts to cover a larger area. Therefore, satellite remote sensing plays an imperative role in agricultural crop monitoring and analysis with the help of desktop-based software tools. Moreover, downloading and analysing satellite imagery is tedious and time-consuming. It requires high computational power and storage space for experimental operations like preprocessing, classification, and visualization of the huge dataset. Additionally, the cost of remote sensing software licenses is very high, whereas computer systems need to be more robust to perform time-series analysis of satellite imagery. Therefore, Google Earth Engine (GEE) provides geoprocessing capabilities for the timeseries dataset in cloud computing. In this research study, we have used vegetation indicators like the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), and the Modified Normalized Difference Water Index (MNDWI) for the crop condition and surface water bodies analysis of the Vaijapur Tehsil for three years from 2021 to 2023. The study shows that The NDVI of the year 2023, categorized as non-vegetation land, damaged, good, and moderate vegetation land, increased by 3.68%, 2.62%, 2.29%, and 1.15%, respectively, while healthy land decreased by 4.60%. The SAVI of 2023 indicated that soil moisture in non-vegetation and moderate land decreased by 1.94% and 4.57%, respectively, while the damaged cropland and good vegetation land increased by 4.62% and 1.86%. The MNDWI of the year 2023 showed that water bodies decreased by 54.96%.

The monitoring and analysis of land surface changes are very challenging for researchers in terms of time and the cost of software tool licenses. Now, it has become easier to accomplish with the help of modern tools like Google Earth Engine (GEE) and built-in Machine Learning (ML) algorithms. GEE is a platform for analysing and interpreting satellite datasets in the cloud, which saves time and storage space for researchers. In the present research study, we have analysed the Land Use Land Cover (LULC) of Vaijapur taluka, which is undergoing a rapid shift from rural to urban. The study compares the LULC classification by three supervised ML algorithms, Random Forest (RF), k- Nearest-Neighbour (k-NN), and Gradient Tree Boost (GTB). We have obtained the overall accuracy of RF (92%) is better than that of GTB (88 %) and k-NN (86.67%). The research study observed that the kappa accuracy of RF (0.89) is improved than GTB (0.83) and k-NN (0.81).