The residential market in Chennai is experiencing growth, yet it faces regulatory challenges, housing affordability issues, flooding, and shifting customer preferences. Developers, investors and financial institutions together with policymakers, must understand how homebuyers’ expectations are evolving. A SWOT evaluation was conducted, survey responses from property buyers and residential developers to establish various market factors impacting the residential market of Chennai. A SWOT analysis using Python programming produced interpretable results from the examined data. The analysis utilized pandas for data manipulation along with sklearn for text vectorization and matplotlib for data visualization to process qualitative responses then turn them into numerical scores by using TF-IDF vectorization and compute cosine similarities. The creation of correlation matrices and visualizations using scatter plots to perform a detailed examination of influences among home-buying choices. These analyses and visualisations cover the alignment gap between the residential promoters and the common respondents of Chennai. It was found that the percentage of dissimilarity is high in the weakness, opportunity and threat categories between the common respondents and the residential promoters. This shows limited overlap between developers’ product offerings and consumer expectations. Consumer choices relied mainly on location combined with affordability, community-friendly living with kids engaging and senior-friendly amenities, quality standards, and flood risk. To succeed in Chennai’s residential market, stakeholders must address market weaknesses and threats, capitalize on opportunities in affordable housing and emerging locations, and adapt to shifting consumer preferences to ensure long-term sustainability.
Livestock farming in the hilly regions of Himachal Pradesh remains highly labour-intensive, with activities such as fodder cutting, tree climbing and dung collection exposing farmers to substantial ergonomic and physiological stress. Steep slopes, limited mechanization and reliance on traditional methods exacerbate fatigue, musculoskeletal strain and reduced productivity, particularly among goat and sheep rearers. To address this, a telescopic walking-cum-fodder cutting tool was developed and ergonomically evaluated. Twenty livestock workers (10 males, 10 females) performed fodder cutting using both conventional tree climbing and the developed telescopic walking-cum-fodder cutting tool. Physiological parameters including Heart Rate (HR), Oxygen Consumption (VO2), Energy Expenditure (EE), Total Cardiac Cost of Work (TCCW), Physiological Cost of Work (PCW) and Overall Discomfort Rating (ODR) were recorded and statistically analysed. The telescopic walking-cum-fodder cutting tool significantly reduced workload: average HR decreased from 167.2 ± 2.3 to 121.6 ± 2.6 bpm (27
The seed spacing measurement is the most crucial step for determining the performance of precision planters in the laboratory. Commonly these measurements are carried out on the sticky belt setup which is time consuming and labor intensive. This study's objective was to develop a sticky belt method substitute that would quickly and automatically assess the precision planter's seed spacing. A direct incidence infrared based embedded seed sensor was developed which consisted of seed sensing unit, circuit board, microcontroller board and Arduino IDE software to work together for seed spacing measurements. The algorithm was developed and deployed in Arduino microcontroller board to read and process the signals from seed sensor and consequently determine the seed spacings. The validation of the developed measurement system was carried out by comparing the values of seed spacings obtained from developed sensing system with that obtained from conventional sticky belt setup. Three types of seeds were metered using pneumatic seed metering unit at different simulated travel speeds of planter. The overall coefficient of determination was 0.994 for all types of seeds and simulated travel speeds. There was no significant difference observed between the two methods of seed spacing measurement. The results indicate that the developed embedded seed sensor could be effectively used to measure the seed spacings in the laboratory for automatic and precise evaluation of precision planters.
Due to early wear of soil-engaging components in tillage implements decreases field efficiency and raises operating costs, accurate wear characterization and life prediction are essential. This study combines controlled soil-bin experiments with field validation to assess the wear behavior and service life of EN42 agricultural discs under Indian soil conditions, overcoming the shortcomings of previous research that only used laboratory or field testing. Different soil types (sand and silty clay loam), moisture levels, and operation speeds were investigated for four commercial EN42 disc variations (M1–M4). Surface hardness (36.3–42.1 HRC), microstructural features, and wear markers such gravimetric loss, radius reduction, and thickness reduction were among the important factors analyzed. Hardness, forward speed, soil type, and moisture content all had a significant impact on wear, according to statistical analysis (p < 0.05). While higher moisture decreased wear in silty clay loam because it improved soil cohesiveness, lower moisture increased abrasive wear in sandy soils. After 100 h of operation, M4 showed the highest performance among the discs, with the lowest cumulative weight loss (547.75 g), radius reduction (1.78 mm), and thickness reduction (0.55 mm). Accurate service life assessment was made possible by regression-based predictive models, which demonstrated high agreement between laboratory and field data (R2 = 0.96). Because of its better microstructure and increased hardness, M4 performs better than M1 and has a service life that is roughly 3.14 times longer.
High-altitude vernacular settlements embody centuries of climate-responsive construction and cultural continuity, yet they are increasingly vulnerable to climate extremes, freeze–thaw cycles, demographic transitions, and accelerating land-use change. While hazard and climate modelling in mountain settlements has advanced considerably, comparatively fewer studies integrate structural vulnerability, environmental exposure, and socio-cultural value into spatially explicit decision frameworks that inform local conservation management. This study addresses that gap by developing an integrated GIS-based vulnerability assessment framework for prioritizing conservation in high-altitude vernacular settlements. Grounded in the exposure sensitivity adaptive capacity paradigm, the framework combines building-height-derived exposure indicators with building-scale structural condition and socio-cultural usage variables to generate a composite, spatially differentiated vulnerability index. To demonstrate its applicability, the framework is implemented in Keylong, a high-altitude Himalayan settlement in Himachal Pradesh, India, comprising 981 vernacular dwellings. Five normalized indices: structural condition, typology, age, height, and socio-cultural usage are aggregated using a weighted multi-criteria approach to compute a Composite Priority Score. Natural-breaks classification delineates three conservation-priority tiers, while ± 5
The study links chlorine decay modeling outcomes with public-health-oriented water quality management by evaluating residual chlorine persistence across the distribution network. Maintaining adequate residual chlorine directly supports safe drinking water provision (SDG 6) and microbial risk reduction (SDG 3), while the modeling framework provides operational decision support for sustainable urban water infrastructure management (SDG 11). Pursuing the goal of guaranteeing safe water quality, this study uses WaterGEMS software to predict the decay kinetics of chlorine in a real-world distribution network. Multiple locations in the research region (Zone A1, Sector 25, Pradhikaran, Nigdi, Pimpri-Chinchwad, Pune, India) were tested for chlorine residuals over five days. We calculated the decay constants for bulk and wall interactions and evaluated the effect of hydraulic factors on chlorine concentration. Chlorotex, Orthotolidine, and DPD tests were used to gather experimental data, which were then compared with findings from WaterGEMS simulations. An R2 value of 0.9644 was observed when plotting 1/(C versus time for a second-order reaction, suggesting that chlorine decay follows second-order kinetics. We found that the average bulk decay coefficient was 0.9581. By integrating field-measured residual chlorine data with WaterGEMS simulations, this study evaluates chlorine decay behavior in a real urban water distribution system and identifies second-order decay kinetics offering system-specific insight into operational chlorine management.
Achieving preferable seismic behaviour of buildings is crucial in critical buildings such as hospitals, which require post-earthquake functionality. This primarily depends on the type of structural system adopted. The current IS 1893 (Part 1) does not explicitly specify the admissible structural system to be adopted for critical buildings, whereas the draft code recommends Wall-Frame Systems (WFS), which include Special Moment Resisting Frames (SMRF) combined with Special Structural Wall (SSW) and Dual Systems. This paper compares the seismic behaviour of low-rise critical RC buildings designed and detailed according to (i) current codes—IS 1893 (Part 1): 2016 IS 13920: 2016, and (ii) draft codes—IS 1893 (Parts 1 2): 2024 and IS 13920 (Parts 1 2): 2024. Fundamental dynamic, nonlinear static, and nonlinear response history behaviour are investigated. The dissipated energy by the structural members is quantified. Further, fragility and damage index curves are developed employing results from Incremental Dynamic Analysis (IDA) to assess and validate the probability of damage and damage state. The performance levels of the buildings are then evaluated. It is observed that WFS designed and detailed as per the draft codes exhibits better seismic behaviour, sustains minor damage and achieves Immediate Occupancy performance, particularly in moderate and high earthquake zones, compared to SMRF systems designed and detailed using current code provisions. In addition, the probability of damage is significantly less in WFS than SMRF systems for the considered damage states, even at high spectral acceleration-inducing events. These findings support the inclusion of WFS for critical buildings, together with minimum structural wall plan density requirements in the draft codes to ensure post-earthquake functionality.
PCWP (Prefabricated Concrete Wall Panels) are characterized by high strength, good durability and a high degree of integration, making them increasingly popular in assembled steel structure buildings. However, due to the high stiffness of these wall panels, they can significantly affect the dynamic characteristics of the structure. This paper tests two three-story steel structure buildings, one with a steel frame-brace structure and the other with a steel frame-shear wall structure, using ambient vibration test methods to obtain their fundamental natural period and damping ratio. Models of the two measured buildings, including the structure and infill walls, are established using ETABS software, with the link element in the models simulating the types of connections between the wall panels and the structure. The fundamental periods obtained from the models are compared with the ambient vibration test results. The research results show that the damping ratio of the measured structures is highly variable and is mostly lower than the design damping ratio specified by the Chinese code JGJ99-2015 for seismic design. The reduction factor for the natural period given in the Chinese code JGJ99-2015 is too large. Based on the comparison between measured results and theoretical calculations, the fundamental period is found to be reduced to 0.81. Considering an additional safety margin, it is recommended that the reduction factor for the natural period can be set at 0.7–0.8. The analysis model established in this paper, which considers the wall panels, is consistent with the measured periods and has good accuracy. Finally, the results of this experiment are compared with the current fundamental period formulas, and it is found that the fundamental period of multi-story steel structure buildings with PCWP can be obtained using the formula proposed by Fang et al.
This paper describes an in-depth case study of St. Andrew’s Church (The Kirk), located in Chennai, India, focusing on its historical background, construction, past damages, repairs, and conservation methodology, with special attention to the steeple, adhering to ISCARSAH principles. A vibration study was conducted to ensure the safe resumption of the church bell’s operation. The Fourier Transform (FT) was employed to understand the response of the steeple to the bell vibrations. The results showed that the maximum PPV was 1.253 mm/s, which is within permissible limits as per codal provisions, indicating that bell operations can be safely resumed without posing any risk to the structure.
Municipal solid waste collection in most Indian cities still relies on fixed-schedule collection and static routing, irrespective of bin fill levels. It often results in overflowing bins in high-waste areas, unnecessary trips to partially filled bins elsewhere, increased fuel consumption, increased operational costs, and environmental pollution. In this study, a hypothetical simulation-based case study of an IoT-enabled smart waste collection and Route Optimization System is designed to support data-driven waste collection planning. Simulated ultrasonic bin level readings were transmitted to a cloud dashboard for real-time monitoring and alert generation. When bin fill levels exceeded a predefined threshold, the Capacitated Vehicle Routing Problem for the shortest-path algorithm was applied to compute an optimized route for waste-collection vehicles. The results demonstrate that the proposed system has reduced total route distance by approximately 35–40
In this study, a robust temperature controller was developed and tested for a solar PV-based electric dryer (SPVED). A cylindrical steel chamber with a diameter of 18.5 cm and a height of 24 cm was selected as a small prototype model for study. The proposed model comprises a solar PV module, a DC-DC buck converter (DCB) and positive-temperature-coefficient (PTC) DC heating coils. Automatic temperature control was implemented in the proposed system by designing a suitable proportional-integral (PI) controller for the DCB with heating coils as the load. The PI controller was tuned using the particle swarm optimization (PSO) algorithm with the integral of time-weighted absolute error (ITAE) as the performance index. The model was tested experimentally with and without solar irradiation using a solar PV module and a DC power source. Under both conditions, the output temperature response of the proposed dryer exhibited a settling time of approximately 7 min, with no overshoot and a deviation of ± 1 °C. The proposed model also demonstrated robustness to variations in solar PV voltage and set-point changes.
Real-time monitoring of safety compliance is a herculean task in the construction scenario especially in vertical construction environments, this paper proposes a novel approach of scaffold-based IoT framework for monitoring construction site safety by addressing altitude detection, harness clamping monitoring. The system is developed in two phases; the first phase addresses the issue of height (altitude-wise) and location detection through RF signal strength and ZigBee technology which achieved a 99.21
Wheat (Triticum aestivum L.) and maize (Zea mays L.) are major staple food crops in India but their cultivation in the state of Himachal Pradesh is constrained by undulated topography, small landholdings and limited mechanization. The present study was undertaken with the aim of examining energy consumption and its efficiency in maize and wheat production under different farm power sources and across varying landholding categories. The input data were collected from 300 farmers across a total of 30 villages in ten out of the twelve districts using an interview-based questionnaire. The collected input energy data such as human power, animal and mechanical power, seed, fertilizers, irrigation, and other field operations were estimated using standard energy equivalent values. The total energy input in maize cultivation varied from 5,271 to 7,444 MJ ha⁻1 with tractor-operated large farms recording the lowest (5,271 MJ ha⁻1), whereas small farms operated with bullocks showed the highest (7,444 MJ ha⁻1) energy consumption. Wheat cultivation required 15–28
Manual planting of ginger rhizomes is a labour-intensive, drudgery-oriented operation. To address this issue, a ginger rhizome planter fitted with a dedicated cup-type seed metering device is needed. A metering cup was designed based on the physical parameters of different ginger rhizome varieties, and its performance was evaluated in laboratory tests. For this study, three different varieties of ginger rhizome, such as Moran (40–50 mm), Nadia (50–60 mm), and Nagaland local (< 40 mm), were collected from Assam, Meghalaya, and Nagaland. The performance of the finger shaped cup (C2) type seed metering device was evaluated against that of the circular metering cup (C1) type seed metering device. The overall experiment was performed by considering three independent parameters, i.e., cup type, rhizome size, and operating speed (1, 1.5 and 2 km/h), and evaluated the performance parameters such as average rhizome spacing, multiple index, missing index, quality of feed index, and physical damage. The ANOVA revealed that all the independent parameters had highly significant effects (p < 0.001) on all performance indices. With increased speed and ginger rhizome size, all performance parameters increased, whereas the quality of feed index (QFI) decreased in both cups. Across all operating conditions, cup, C2 performance is better than C1, with lower missing index, damage and higher QFI. The maximum QFI of 95
This study presents a multi-stressor physics of failure framework for computing site specific reliability and remaining useful life (RUL) of pole luminaire systems subjected to the coupled effects of wind induced vortex shedding, thermal cycling, and atmospheric corrosion. A time dependent reliability index is formulated by integrating fatigue damage modelling through Miner’s cumulative damage rule and S–N fatigue characterisation with first order reliability methods (FORM). The effective stress is obtained by superposing dynamic wind induced alternating stress, quasi-static thermal mean stress, and corrosion-amplified stress arising from progressive section loss, combined through the Goodman fatigue criterion. The framework incorporates location specific environmental data wind climatology, diurnal temperature ranges, relative humidity, and sulphate/chloride deposition to generate spatially resolved RUL curves and failure probability trajectories. A comparative reliability analysis across three standard pole geometries square straight steel (SSS), round straight steel (RSS), and round tapered steel (RTS) demonstrates that SSS poles exhibit the highest fatigue vulnerability, with a representative 5-year failure probability of 10.74
This paper explores latent perceptual constructs that define private vehicle commuters’ intention to adopt EVs, using a cross-sectional survey combining stated and revealed preference data across two Indian metropolitan areas. Twenty-seven perception-based variables, based on economic, technological, infrastructural, environmental, social and policy dimensions, were synthesized using Principal Component Analysis (PCA) into five, theoretically coherent constructs. These latents were later incorporated into predictive machine learning models, including Support Vector Machines (SVM), XGBoost, k-Nearest Neighbors (KNN), and an Artificial Neural Network (ANN) of EV adoption readiness based on behavioral intention theories. SHAP-based explainability identified perceived reliability, infrastructure readiness, and policy stability as the most common factors to predict adoption intention. Factorial scenario simulations indicated substantial interaction effects and that combined policy interventions had a greater effect on non-adoption probabilities than isolated improvements. The results highlight the importance of combining dimensionality reduction, nonlinear predictive modeling and explainable AI to provide insights for evidence-based approaches to EV adoption in emerging economies.
Landfills are of prime importance in developing countries for waste management. However, in case of non-engineered landfills, leachate percolating down through its layers pose an ultimate pollution threat to both ground and surface water resources. The present study focuses on the assessment of groundwater quality in the vicinity of a landfill to examine the potential impact of the landfill on the groundwater. Ghazipur landfill is selected for the study, and thereby, ten sites have been examined for the water quality parameters. Groundwater quality analysis revealed elevated concentrations of TDS (455–1160 mg/L), Alkalinity (206–600 mg/L), Hardness (180–520 mg/L), Chloride (40–365 mg/L), BOD (2.5–10 mg/L), COD (26–48 mg/L), Zn (0.4–1 mg/L), Cadmium (0.01–0.05 mg/L), and Lead (0.04–0.07 mg/L). All the parameters (except pH) at most of the locations were found to exceed the Indian standard values for drinking water. Statistical analysis further highlighted strong inter-parameter relationships (Pearson coefficient > 0.90) and good R2 values (0.66–0.97) for most of the parameters, suggesting a common source of origin and distance-based dilution of contamination. Sampling location S6 in the North was found to be the most contaminated location, and location S4 in the East was the least contaminated location. The major finding of the study indicates that heavy metals—lead and cadmium metals lie significantly above standard levels, which need to be addressed on a priority basis, due to their substantial health risks. Contour maps around the landfill suggested that the groundwater in areas immediately next to the landfill is not suitable for drinking; however, zone suitability for drinking increased with an increase in distance from the landfill.
Design of pile foundations in heterogeneous soils is largely controlled by the in-situ soil properties and stratigraphy of the construction site. The present study aims to evaluate the influence of stratigraphic variability on pile capacity using Standard Penetration Test (SPT) and Cone Penetration Test (CPT) field data obtained from a 950 m stretch of a dam construction site. The stratigraphic profile of the construction site was developed using SPT data from 25 boreholes and CPT data from 20 test locations. The allowable load-carrying capacities of driven precast piles at various locations across the construction site were estimated using GEO5 software. The analyses were performed independently based on corrected SPT values (Ncorr) and CPT data, including cone resistance and sleeve friction. A uniform pile length of 18 m, along with pile diameters of 0.5 m and 0.75 m, was adopted for the estimation of allowable load-carrying capacities of piles. Additionally, widely used empirical correlations between SPT and CPT parameters were evaluated to assess their suitability for the site’s stratigraphic conditions. Significant variations were observed in zones where transitions between clayey and sandy strata occur, emphasising the influence of stratigraphic heterogeneity on the mobilisation of shaft and end-bearing resistance. A comparison of SPT-based and CPT-based capacity estimates indicated that stratigraphic variability plays a significant role in interpreting in-situ test data for pile design. The importance of stratigraphic characterisation for reliable estimates of pile capacity under heterogeneous soil conditions is highlighted in this study.
The need to enhance the yield of postharvest processing of food grains stimulated this research interest to confront the associated inefficiencies in groundnut peeling or decortication. The objective of this work is to analyze system performance with a focus on the optimisation of the peeling process for better efficiency. The study applied the response surface technique and a central composite design (CCD) to analyze the influence of varying feed weights (A: 0.3, 0.6, 0.9, and 1.2 kg) and rotor speeds (B: 150, 200, 250, and 300 rpm) on a groundnut decorticator's ability to peel. Key performance metrics such as peeling efficiency, throughput capacity, peeling time, material capacity, and kernel damage efficiency were damaged. Analysis of variance (ANOVA) and other statistical techniques were performed to evaluate the model's adequacy and variable significance. Numerical optimization was carried out via a desirability index method to determine the optimum peeling process. Models were developed to predict the peeling efficiency, peeling time, and throughput capacity, with the coefficients of determination varying from 0.8837 to 0.9497. Statistical evaluation of the experimental variables and normal probability plots of peeling efficiency, throughput capacity, and peeling time residuals validated the models. The findings revealed that the peeling efficiency, peeling time, kernel damage, and throughput capacity of the system were significantly (P < 0.05) affected by both feed weight and rotor speed and varied from 78.8 to 91.2
