Abstract Remote sensing land cover classification plays a crucial role in detecting changes, urbanization planning, mapping and monitoring on earth surface. It is very challenging to get accurate result remote data because different classifiers are much area dependent. Different such as decision tree (DT), K-nearest neighbor (KNN), artificial neural network (ANN), support vector machine (SVM), boosted (BDT), random forest (RF), regression (CART) maximum likelihood (MLC), have accuracies for...

Plant diseases present a substantial threat to global food security, and the timely detection of such remains challenging time-consuming task. The accurate determination plant's health status identification specific infections typically require expertise professionals. advent Deep Learning has significantly transformed field computer vision, offering highly efficient techniques for image analysis categorization. This study specifically focuses on utilizing MobileNet50 Convolutional Neural...

Abstract It is vital for public awareness and decision-makers to investigate the impact caused by changes in urban land use cover on ecosystem service values (ESVs) order promote sustainable development, protect environment, health, ensure communities’ long-term well-being. Changes services brought (LULC) are a crucial early indicator warning sign of ecological shifts. Using remote sensing GIS tools, this study examined shifting dynamics ESVs Haridwar district Uttarakhand state, India. The...

The implementation of the security system for all devices is through passive communication technology. People from different origins and regions need a their platforms. convincing type that it makes sure works under proper guidance natural care system. leverage to make them work conditions defined process. One-time password-based technology also used other surveillance process wholly monitored by one-time theme. major done superior convenience successive devices. metropolitan areas which are...

This research paper introduces a novel methodology that employs Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) to classify grapevine leaf diseases. A complete dataset consisting of photos leaves exhibiting different illnesses healthy conditions was gathered subjected preprocessing techniques assure consistency improve the resilience model. The design Network (CNN) comprised three convolutional layers, succeeded by max-pooling culminated in solitary fully connected...

Retinal microvascular is a dependable marker of abnormalities in vessel morphology, that have been linked to variety clinical disorders, both ocular and metastatic disease. However, accurate segmentation, which would be intricate- time-intensive, required for objective statistical evaluation the retinal blood vessels. In terms segmenting vessels, artificial intelligence (AI) has shown significant amount promise. this study, fundus images segmented using deep learning methods. The data set...

Blockchain systems' credibility is severely damaged by flaws. A thorough understanding of blockchain vulnerabilities crucial for developing effective methods preventing, detecting, and remediating them. In this study, we employ statistical to compare the bug populations eight popular public projects. The first step a human review 500 reports see what sorts problems have been reported. Second, utilize card sorting divide reported into seven distinct categories that can all be found in...

The design and implementation of Underwater Wireless Optical Communication (UWOC) provide important scientific problems. UWOC has the ability to transmit data at a high pace across long distances. This essay makes an effort concentrate on complexity real-world applications unresolved problems in systems. key developments advancements subject, modelling methods, connection difficulties are outlined. goal this study is recommendations for practical trustworthy with enhanced performance....

Agriculture is critical to the global economy, therefore introduction of automation in this field now an essential and rising topic internationally. Demands for food labor are at exponential rate, outpacing capabilities conventional farming practices. A new age revolutionary change has been caused by incorporation Artificial Intelligence (AI) into agriculture. This study focuses on development AI-powered Chatbot that customized agricultural sector, offering assistance with crop...

Pneumonia is still considered as a major worldwide healthcare hazard which needs immediate treatment and timely precise identification. The research paper shows the method for identification of disease with use Convolutional Neural Network (CNN) on Chest X-ray(CXR) images help Batch normalisation, padding data augmentation. uses comprehensive dataset 3450 CXR images. experiments were conducted over 200 epochs to ensure accuracy. normalization contributed stability better interpretability...

The identification of faults in traditional approaches often depends on intricate algorithms and considerable preparation data. On the other hand, decision tree classifiers provide a more simple but effective method for automated fault classification. aim this study is to evaluate how well Decision Tree Classifier performs field detecting categorizing electrical faults. Electrical systems are vulnerable multitude errors that have potential compromise dependability security whole...

Stock market forecasting is a crucial element of financial systems, yet it may be tough to anticipate marketplace trends because the loud & non-stationary nature data. Deep learning known for extracting superior conceptual properties from massive amounts actual data without relying upon previous information, which useful in predicting activities. This paper seeks offer deep system that automatically mines statistic laws material and directs stock operations using bottom neural network models...

Abstract Analysing and predicting changes in land use/ cover (LU/LC) is a very essential study for decision makers to manage control environmental sustainability by assessing the effects of global climate change. This study, aims evaluate LULC last two decades from 2000 2020, as well as, predict 2030 using Google Earth Engine IDRISI software. Random Forest classification scheme GEE used classifying covers. Based upon 2010 classified maps, “transition probability” matrix determined SILVA 17.0...

A unique, developing idea known as "smart cities" relies on cutting-edge information and communication systems. Policy makers frequently require precise updated land use cover data to effectively represent the city. After forming a new state Uttarakhand from Uttar Pradesh, Dehradun district, capital of state, witnessed rapid fluctuations in (LULC) especially with reference built-up area due smart city project (urbanization). This research article reveals impact efficiency by using remote...

In a period characterised by increasing apprehensions about the environment and limited resources, need to shift from linear inefficient model circular sustainable one is of utmost importance. The publication titled ‘From Waste Worth: A Comprehensive Approach Resource Utilisation Minimization’ delves into complex interrelationships among materials, energy, waste management. This detailed analysis explores importance achieving closed-loop systems in our economic industrial sectors, with...