Journal of Scientific Research and Technology

Air Quality Prediction Using Machine Learning Techniques: A Case Study On Sulphur Dioxide Forecasting

2025-09-02T20:09:34+00:00

Air pollution is one of the greatest problems being faced by mankind. Millions of people die each year because of reasons directly or indirectly related to air pollution. Effective strategies to counter the harmful effects of air pollution are an imperative need of the times. The responses to the air pollution problems are usually knee-jerk reactions, which don’t help in the long run. For developing an effective counter-strategy for combating air pollution, it is necessary to focus the efforts on the pollutants that are most responsible for the air pollution. Examining and protecting air quality has become one of the most essential activities for the government in many industrial and urban areas today. The meteorological and traffic factors, burning of fossil fuels, and industrial parameters play significant roles in air pollution. With this increasing air pollution, We are in need of implementing models which will record information about concentrations of air pollutants(so2,no2,etc).The deposition of this harmful gases in the air is affecting the quality of people’s lives, especially in urban areas. Lately, many researchers began to use Big Data Analytics approach as there are environmental sensing networks and sensor data available. In this project, machine learning techniques are used to predict the concentration of so2 in the environment. Sulphur dioxide irritates the skin and mucous membranes of the eyes, nose, throat, and lungs. Models in time series are employed to predict the so2 readings in nearing years or months.

Evaluating The Potential Of Biochar As Landfill Liner For Leachate Prevention

2025-09-10T18:29:42+00:00

This project aims is to create a of biochar based landfill liner. Leachate, a byproduct of landfill waste, contains various
hazardous substances that can pollute the surrounding environment if not managed properly. Traditional landfill liners
made of synthetic materials have been effective in preventing leachate seepage, but they are costly and can have negative
environmental impacts. Biochar, a type of charcoal produced from organic material (Sewage sludge in our case), has
been identified as a promising alternative liner material due to its high porosity and adsorption capacity. In this project
we plan on conducting laboratory experiment to test the effectiveness of biochar as a landfill liner material.

Classification Of Wheat Disease Using CNN

2025-09-14T04:03:49+00:00

Leaf rust, stem rust, and powdery mildew are just a few of plant diseases that may drastically reduce the productivity of wheat, a cereal crop that is crucial on a worldwide scale. In order to intervene quickly and implement sustainable farming techniques, early and precise disease diagnosis is essential. Automated disease classification in wheat utilizing CNN is presented in this paper as a deep learning-based technique. In order to make the model more generalizable, it was preprocessed and enhanced using a dataset of wheat leaf photos that included images of various diseases. Input photos were used to train a bespoke CNN architecture that could learn hierarchical features. Model's strong performance in differentiating amongst infected and healthy wheat samples was shown by its high classification accuracy. In terms of accuracy, recall, and total F1-score, CNN model outperforms conventional machine learning classifiers. With suggested approach, agronomists and farmers may have access to a scalable and effective tool for early disease identification in wheat, which would allow for more precise treatment and less yield loss.

Advanced Railway Track Fault Detection Using Internet Of Things (Iot)

2025-09-14T20:28:01+00:00

System advancement in railway sector has also resulted in the increase of railway traffic. Because of this the number of accidents in trains/railways have also increased. Every year, almost 11 million passengers travel by train. It is therefore very much important Railway is the backbone of transport system in India. Rail accidents occur more due to derailments than collision or fire in trains. These derailments are due to cracks in the railway tracks. Therefore, there is an immense need of crack detection and security system. This paper proposes the crack detection system in the rail tracks. This is to avoid rail accidents by using latest communication technologies. In this project GSM communication protocols are used to convey the message of crack detection via SMS. Crack detection is achieved by using the concept of eddy current losses implemented in the terms of Darlington pair circuit. With the detection of cracks, the system also alerts the railway authorities facilitating the security to involve such kind of technology which reduces the train accidents and hence human’s life. This paper is the analysis of various critical and unwanted situation, accidents, occurs in train system and how to prevent those accidents. In our paper we have included various approaches done by various researchers in order to avoid train accidents.

Conjunctivitis of Eye Detection Using CNN

2025-09-14T20:41:42+00:00

Conjunctivitis, commonly known as "pink eye," is a highly contagious inflammation of the conjunctiva that affects millions globally each year. Early and accurate detection is crucial for effective treatment and to prevent widespread transmission. Traditional diagnosis relies heavily on physical examination and clinical expertise, which may be time-consuming and prone to human error. This paper proposes an automated Conjunctivitis detection system using Convolutional Neural Networks (CNN), a deep learning technique well-suited for image classification tasks. The proposed model is trained on a curated dataset of eye images labeled as normal or conjunctivitis-infected. The CNN architecture extracts hierarchical visual features and learns patterns associated with conjunctivitis, enabling robust classification. The system achieves high accuracy in detecting infected eyes, providing a rapid, non-invasive, and scalable diagnostic tool. This approach has the potential to support ophthalmologists in early screening and can be deployed in GUI-based applications.

Noise Pollution Monitoring of Residential Areas In Sedam Taluka Kalaburgi Districts

2025-09-15T19:37:40+00:00

Sound which is undesirable for human hearing is called as noise. When there is a lot of noise from various sources, it constitutes what is called as noise pollution. Noise pollution can be caused due to various sources there is street noise, traffic noise, and noise in public transport places, noise in playgrounds and parks etc.. One of the greatest sources of noise pollution is Heavy vehicles like Trucks and Buses. The Noise level in Sedam Taluka of Kalaburgi District of Karnataka, India has been increasing rapidly due to rapid urbanization, uncontrolled movements of vehicles.

In this paper we are trying to present about the result of noise level in dB (A) on various points of sedam Taluka of Kalaburgi District. It has been found out that noise levels are more than permissible in all the investigated various spots around the Sedam Taluka.

The minimum noise level by taking into account of morning, afternoon & evening hours is 60.30dB and the maximum noise level of morning, afternoon & evening is 76.88dB and the average of both is 68.83dB, which is more than the limits compared to CPCB Standards. Result shows, the noise should be identified as the major environmental problem and should take necessary steps to minimize it.

Noise Pollution Monitoring of Residential Areas In Jewargi Town Kalaburgi District

2025-09-15T20:02:16+00:00

Sound which is undesirable for human hearing is called as noise. When there is a more noise from various sources, it constitutes what is called as noise pollution. Noise pollution can be caused due to various sources there is street noise, traffic noise, and noise in public transport places, noise in playgrounds and parks etc.. One of the greatest sources of noise pollution is Heavy vehicles like Trucks and Buses. The Noise level in Jewargi Taluka of Kalaburgi District of Karnataka, India has been increasing rapidly due to rapid urbanization, uncontrolled movements of vehicles.

In this paper we are trying to present about the result of noise level in dB (A) on various points of Jewargi Town of Kalaburgi District. We have came to know that noise levels are more than permissible in all the investigated various spots around the Jewargi Town.

The minimum noise level by taking into account of morning, afternoon & evening hours is 60.82dB and the maximum noise level of morning, afternoon & evening is 76.70dB and the average of both is 68.75dB, which is more than the limits compared to CPCB Standards. Result shows, the noise should be identified as the major environmental problem and should take necessary steps to minimize it.

Noise Pollution Monitoring And Control At Chitapur Town Kalaburagi

2025-09-15T20:15:10+00:00

Noise pollution can be divided into three groups industrial noise, community noise and traffic noise. In the case of traffic noise, major portion of traffic noise is contributed by heavy vehicles (Commercial Trucks and Buses) only. An uncontrolled movement of these heavy vehicles in the town creates so called 'traffic jam' and finally creates noise. In this paper we are trying to know about the values of noise pollution at the various locations of Chittapur town kalaburagi district. And all the values we have got after survey are more than CPCB standards during Morning, Afternoon and Evening hours. Which is not good for the environment and for the human being, so the suggestions are given to reduce the noise levels as much as possible.

A Study on Mechanical and Tribological Properties of Aluminum 7068 MMCS Reinforced with Silicon Carbide and Biochar by Stir Casting Process

2025-09-15T20:23:31+00:00

The present study focuses on the development and characterization of Aluminum 7068 metal matrix composites (MMCs) reinforced with Silicon Carbide (SiC) and Biochar using the powder metallurgy process. Aluminum 7068, known for its high strength-to-weight ratio, was selected as the base material, while SiC was introduced to enhance hardness and wear resistance, and Biochar was added as a sustainable reinforcement to improve mechanical and tribological behavior. The fabricated composites were subjected to microstructural analysis, hardness testing, tensile strength evaluation, and wear studies. Results are expected to demonstrate improved hardness, strength, and wear resistance with the hybrid reinforcement, highlighting the potential of combining SiC and Biochar as effective reinforcements. This study contributes to developing lightweight, eco-friendly, and high-performance materials for aerospace, defense, and automotive applications.

Impact Of Plan Irregularities On Performance Of Building Subjected To Seismic Load

2025-09-16T20:49:25+00:00

The present study, investigates the impact of different types of plan irregularities on the building subjected to seismic force. The L, H, T, U Shaped plan irregular building are moderate in ETABS software, then seismic load along with gravity load is assigned as per IS codes. The equivalent static method is used for analysis. The study confirms that plan irregularities play a critical role in determining seismic performance, and among the studied configurations, the T-shaped structure shows the most suitable for resisting earthquake-induced forces. These results provide valuable insights for engineers and designers in optimizing irregular building layouts for both functionality and resilience.

Evaluation Of Phytoconstituents In Edible White Button Mushroom Agaricus Bisporus

2025-09-18T17:58:07+00:00

Significant secondary metabolites were found in Agaricus bisporus after a qualitative phytochemical screening in this investigation. Flavonoids, phenols, saponins, glycosides, and tannins are examples of phytochemical substances that are thought to be important secondary metabolites in mushrooms. Alkaloids, carbohydrates, glycosides, proteins, phenols, flavonoids, saponins, terpenoids, cardiac glycosides, tannins, and steroids were all detected in the extracts during the initial screening process. According to HPLC, the main components in the methanol extract of A. bisporus were gallic acid and ergothioneine, respectively. These active metabolites are well known for their ability to treat a variety of human conditions, including menstrual disorders, chronic eczema, diarrhoea, dysentery, spasmodic, and diuretic-choleretic. Depending on the molecular formula, retention time-molecular weight, and peak area, our HPLC data indicate the existence of various bioactive substances. Its antibacterial, antidiabetic, and antioxidant qualities may be attributed to the primary phytochemical components found in A. bisporus, which have been identified in the current work. The initial results demand more thorough research, including in vitro tests. Thus, the mushroom employed in this study may find application in the pharmaceutical business for a variety of medical purposes.

HPTLC fingerprinting of Azadirachta indica leaf and bark extracts and their antimicrobial activity against Escherichia coli

2025-09-18T18:28:56+00:00

The Meliacea family includes Azadirachta indica L., popularly referred to as "neem," which is extensively accessible throughout the Indian subcontinent. The neem tree is well-known for its many medicinal uses, including as an insecticide, pesticide, antidiabetic, antibacterial, and antiparasitic. The plant's leaves are frequently employed in "kwath" and "churna," two Ayurvedic preparations. It is crucial to standardise and record the quality criteria of the plant leaves because of their great medicinal potential and to evaluate the scientific research on Azadirachta indica's utilisation. Aqueous extracts of the plant's dried leaves and bark were tested for antimicrobial activity against gram-negative Escherichia coli bacteria. Using a solvent system of toluene: ethyl acetate: formic acid 5:4:0.2, the ethanolic extract of dried powdered leaves and bark was assessed by HPTLC fingerprinting, which shows the identities of the chemicals included in the extracts. By measuring the width of the zone of inhibition against the bacteria using the agar well diffusion technique, the antimicrobial activity of the concentrated extracts was assessed. In both aqueous extracts, the bark and leaves of A. indica showed antibacterial action against E. coli. The different zones of inhibition with concentration changes demonstrated that the antibacterial activity of A. indica extracts was concentration-dependent. According to the study's findings, Azadirachta indica leaves can be used as an alternative medical system to treat a variety of microbial illnesses.

Evaluation of Phytoconstituents Swertia chirayita for its Antidiabetic properties

2025-09-18T18:39:26+00:00

Swertia chirayita is a medicinal plant with a rich history in traditional Ayurvedic medicine. This article explores the various bioactive compounds present in Swertia chirayita, such as flavonoids and terpenoids. These compounds are thought to be responsible for the plant's noted antioxidant, anti-diabetic, antibacterial, and anticancer properties. A qualitative phytochemical screening in this study revealed significant secondary metabolites in Swertia chirayita, including flavonoids, phenols, saponins, glycosides, and tannins, which are considered important secondary metabolites of the plant. The initial screening process detected various substances in the extracts, including alkaloids, carbohydrates, glycosides, proteins, phenols, flavonoids, saponins, terpenoids, tannins, and steroids. These active metabolites are well-documented for their efficacy in addressing various human ailments, including menstrual disorders, chronic eczema, diarrhoea, dysentery, spasmodic conditions, and as diuretic-choleretic agents. Swertia Chirayata extracts from Swertia chirayata may help manage diabetes. It was corroborated by the fact that Swertia chirayata inhibited α-amylase activity at 59.36 ± 1.42 µg/ml and α-glucosidase activity at 28.12 ± 1.34 µg/ml. In summary, the antidiabetic qualities of Swertia chirayata make them potential candidates for a functional food or natural supplement. The antibacterial, antidiabetic, and antioxidant properties of Swertia chirayita may be attributed to the primary phytochemical components identified in this investigation. The preliminary findings indicate a need for further research, including in vitro studies. Consequently, Swertia chirayita, examined in this study, may have valuable applications in the pharmaceutical industry for various medical uses. Finally, the limitations of current research and the need for further studies are addressed.