This document discusses a proposed system for predicting traffic flow using big data and classification approaches. The system uses K-Nearest Neighbors (KNN) classification to identify traffic patterns and routes. It then uses a Convolutional Neural Network (CNN) to predict traffic flow levels on particular routes. The KNN identifies travel times between locations while the CNN predicts flow levels. The proposed system is evaluated using metrics like root mean squared error and mean relative error, and is found to improve accuracy and reduce prediction time compared to existing methods. The system aims to provide route recommendations to users based on minimum predicted traffic flow.
Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman fil...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
DEEP LEARNING NEURAL NETWORK APPROACHES TO LAND USE-DEMOGRAPHIC- TEMPORAL BA...civejjour
Land use and transportation planning are inter-dependent, as well as being important factors in forecasting urban development. In recent years, predicting traffic based on land use, along with several other variables, has become a worthwhile area of study. In this paper, it is proposed that Deep Neural Network Regression (DNN-Regression) and Recurrent Neural Network (DNN-RNN) methods could be used to predict traffic. These methods used three key variables: land use, demographic and temporal data. The proposed methods were evaluated with other methods, using datasets collected from the City of Calgary, Canada. The proposed DNN-Regression focused on demographic and land use variables for traffic prediction. The study also predicted traffic temporally in the same geographical area by using DNN-RNN. The DNN-RNN used long short-term memory to predict traffic. Comparative experiments revealed that the proposed DNN-Regression and DNN-RNN models outperformed other methods.
This white paper presents a spatial decision support system (SDSS) aimed at generating optimized vehicles routes for multiple vehicles routing problems that involves serving the demand located at nodes of a transportation network. The SDSS incorporates MapPointTM (cartography and network data), a database and a metaheuristic developed generate routes.
Improving transport in Malta using GIS and LBSMatthew Pulis
A presentation prepared to the University of Malta as part of my MSc. Informatics. This seminar discusses ways and improvements how can a GIS driven system help and improve the current situation in Malta. This presentation also provides a survey discussing how the Maltese view the public transport and gives out interesting conclusions as to where the GIS needs to tackle. The study focuses mainly on ways as to where and how to improve the routes, promoting cultural places, buses ETA and taxi fleet handling amongst others.
This paper proposes algorithms for dynamic travel time prediction to provide reliable real-time
travel time information using probe travel time data collected by a dedicated short range communication (DSRC)
system. The travel time predictions were performed using arrival-time-based travel time; subsequently, the
accuracy of these predictions was evaluated using the concurrent departure-time-based travel time data, which
were also collected by the DSRC system. The prediction methodologies proposed in this research include the
Kalman filter and a newly developed algorithm that uses weighting factors according to probe sample size. An
evaluation of the performance of the two algorithms showed their errors ranged from 5 to 7%, thereby showing
satisfactory results. Considering the fact that the Kalman filter requires historical travel time for prediction, the
similarity between the historical and current data is core factor for reliable travel time prediction. On the other
hand, the newly developed algorithm does not need historical data, thereby the benefit could be enhanced
especially when historical travel time data analogous to current ones are not easily available.
Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman fil...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
DEEP LEARNING NEURAL NETWORK APPROACHES TO LAND USE-DEMOGRAPHIC- TEMPORAL BA...civejjour
Land use and transportation planning are inter-dependent, as well as being important factors in forecasting urban development. In recent years, predicting traffic based on land use, along with several other variables, has become a worthwhile area of study. In this paper, it is proposed that Deep Neural Network Regression (DNN-Regression) and Recurrent Neural Network (DNN-RNN) methods could be used to predict traffic. These methods used three key variables: land use, demographic and temporal data. The proposed methods were evaluated with other methods, using datasets collected from the City of Calgary, Canada. The proposed DNN-Regression focused on demographic and land use variables for traffic prediction. The study also predicted traffic temporally in the same geographical area by using DNN-RNN. The DNN-RNN used long short-term memory to predict traffic. Comparative experiments revealed that the proposed DNN-Regression and DNN-RNN models outperformed other methods.
This white paper presents a spatial decision support system (SDSS) aimed at generating optimized vehicles routes for multiple vehicles routing problems that involves serving the demand located at nodes of a transportation network. The SDSS incorporates MapPointTM (cartography and network data), a database and a metaheuristic developed generate routes.
Improving transport in Malta using GIS and LBSMatthew Pulis
A presentation prepared to the University of Malta as part of my MSc. Informatics. This seminar discusses ways and improvements how can a GIS driven system help and improve the current situation in Malta. This presentation also provides a survey discussing how the Maltese view the public transport and gives out interesting conclusions as to where the GIS needs to tackle. The study focuses mainly on ways as to where and how to improve the routes, promoting cultural places, buses ETA and taxi fleet handling amongst others.
This paper proposes algorithms for dynamic travel time prediction to provide reliable real-time
travel time information using probe travel time data collected by a dedicated short range communication (DSRC)
system. The travel time predictions were performed using arrival-time-based travel time; subsequently, the
accuracy of these predictions was evaluated using the concurrent departure-time-based travel time data, which
were also collected by the DSRC system. The prediction methodologies proposed in this research include the
Kalman filter and a newly developed algorithm that uses weighting factors according to probe sample size. An
evaluation of the performance of the two algorithms showed their errors ranged from 5 to 7%, thereby showing
satisfactory results. Considering the fact that the Kalman filter requires historical travel time for prediction, the
similarity between the historical and current data is core factor for reliable travel time prediction. On the other
hand, the newly developed algorithm does not need historical data, thereby the benefit could be enhanced
especially when historical travel time data analogous to current ones are not easily available.
Accessibility Analysis and Modeling in Public Transport Networks - A Raster b...Beniamino Murgante
Accessibility Analysis and Modeling in Public Transport Networks - A
Raster based Approach
Morten Fuglsang, - National Environmental Research Institute, Aarhus
University and Aalborg University Copenhagen
Henning Sten Hansen - Aalborg University Copenhagen
Bernd Münier - National Environmental Research Institute, Aarhus University
The Seaport Service Rate Prediction System: Using Drayage Truck Trajectory Da...Meditya Wasesa
This file elaborates how drayage (truck) operators can apply predictive analytic techniques to their internal data assets to extract better insights and improve their operational decision making. For more detail please find our Decision Support Systems journal article at http://dx.doi.org/10.1016/j.dss.2016.11.008
Utilizing GIS to Develop a Non-Signalized Intersection Data Inventory for Saf...IJERA Editor
Roadway data inventories are being used across the nation to aid state Departments of Transportation (DOTs) in decision making. The high number of intersection and intersection related crashes suggest the need for intersection-specific data inventories that can be associated to crash occurrences to help make better safety decisions. Currently, limited time and resources are the biggest difficulties for execution of comprehensive intersection data inventories, but online resources exist that DOTs can leverage to capture desired data. Researchers from The University of Alabama developed an online method to collect intersection characteristics for non-signalized intersections along state routes using Google Maps and Google Street View, which was tied to an Alabama DOT maintained geographic information systems (GIS) node-link linear referencing method. A GIS-Based Intersection Data Inventory Web Portal was created to collect and record non-signalized intersection parameters. Thirty intersections of nine different intersection types were randomly selected from across the state, totaling 270 intersections. For each intersection, up to 78 parameters were collected, compliant with the Model Inventory of Roadway Elements (MIRE) schema. Using the web portal, the data parameters corresponding to an average intersection can be collected and catalogued into a database in approximately 10 minutes. The collection methodology and web portal function independently of the linear referencing method; therefore, the tool can be tailored and used by any state with spatial roadway data. Preliminary single variable analysis was performed, showing that there are relationships between individual intersection characteristics and crash frequency. Future work will investigate multivariate analysis and develop safety performance functions and crash modification factors.
A Parallel Computing Model for Segmentation of Vehicle Number Plate through W...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Transit Signalisation Priority (TSP) - A New Approach to Calculate GainsWSP
Presentation by François Bélisle, Eng. , B.Sc., M.A. and Stephan Kellner, Eng., P.Eng., MS delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30.
A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Inter...ijtsrd
In this paper, a two stage fuzzy logic system has been proposed to control an isolated intersection adaptively. The aim of this work is to minimize the average waiting time for a different traffic flow rates in real time means. In the first stage, the system consists of two modules named next phase selection module and the green phase extension module. In the second stage the system consists of the decision named module. The study was performed using SUMO traffic simulator. A comparison is made between a fuzzy logic controller and a conventional fixed time controller. As a result, fuzzy logic controller has shown better performance. Taha Mahmood | Muzamil Eltejani Mohammed Ali | Akif Durdu ""A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Intersection Based on Real Data using SUMO Simulator"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23873.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/23873/a-two-stage-fuzzy-logic-adaptive-traffic-signal-control-for-an-isolated-intersection-based-on-real-data-using-sumo-simulator/taha-mahmood
DYNAMIC RESOURCE ALLOCATION IN ROAD TRANSPORT SECTOR USING MOBILE CLOUD COMPU...IAEME Publication
Literature review revealed application of various techniques for efficient use of existing resources in road transport sector vehicles, operators and related facilities. This issue assumes bigger dimensions in situations where there are multiple routes and the demand in the routes is highly fluctuating over the day. The application of the existing techniques as reported in literature addresses above issues to a considerable extent. However the main draw back in existing techniques is lack of
proper uninterrupted information about vehicles and demand available at a central place for allocation of vehicles in different roads and huge computational times required for processing. Cloud computing is a recently developed processing tool that is used in effective utilization of resources in transport sector under dynamic resource allocation.
Accessibility Analysis and Modeling in Public Transport Networks - A Raster b...Beniamino Murgante
Accessibility Analysis and Modeling in Public Transport Networks - A
Raster based Approach
Morten Fuglsang, - National Environmental Research Institute, Aarhus
University and Aalborg University Copenhagen
Henning Sten Hansen - Aalborg University Copenhagen
Bernd Münier - National Environmental Research Institute, Aarhus University
The Seaport Service Rate Prediction System: Using Drayage Truck Trajectory Da...Meditya Wasesa
This file elaborates how drayage (truck) operators can apply predictive analytic techniques to their internal data assets to extract better insights and improve their operational decision making. For more detail please find our Decision Support Systems journal article at http://dx.doi.org/10.1016/j.dss.2016.11.008
Utilizing GIS to Develop a Non-Signalized Intersection Data Inventory for Saf...IJERA Editor
Roadway data inventories are being used across the nation to aid state Departments of Transportation (DOTs) in decision making. The high number of intersection and intersection related crashes suggest the need for intersection-specific data inventories that can be associated to crash occurrences to help make better safety decisions. Currently, limited time and resources are the biggest difficulties for execution of comprehensive intersection data inventories, but online resources exist that DOTs can leverage to capture desired data. Researchers from The University of Alabama developed an online method to collect intersection characteristics for non-signalized intersections along state routes using Google Maps and Google Street View, which was tied to an Alabama DOT maintained geographic information systems (GIS) node-link linear referencing method. A GIS-Based Intersection Data Inventory Web Portal was created to collect and record non-signalized intersection parameters. Thirty intersections of nine different intersection types were randomly selected from across the state, totaling 270 intersections. For each intersection, up to 78 parameters were collected, compliant with the Model Inventory of Roadway Elements (MIRE) schema. Using the web portal, the data parameters corresponding to an average intersection can be collected and catalogued into a database in approximately 10 minutes. The collection methodology and web portal function independently of the linear referencing method; therefore, the tool can be tailored and used by any state with spatial roadway data. Preliminary single variable analysis was performed, showing that there are relationships between individual intersection characteristics and crash frequency. Future work will investigate multivariate analysis and develop safety performance functions and crash modification factors.
A Parallel Computing Model for Segmentation of Vehicle Number Plate through W...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Transit Signalisation Priority (TSP) - A New Approach to Calculate GainsWSP
Presentation by François Bélisle, Eng. , B.Sc., M.A. and Stephan Kellner, Eng., P.Eng., MS delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30.
A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Inter...ijtsrd
In this paper, a two stage fuzzy logic system has been proposed to control an isolated intersection adaptively. The aim of this work is to minimize the average waiting time for a different traffic flow rates in real time means. In the first stage, the system consists of two modules named next phase selection module and the green phase extension module. In the second stage the system consists of the decision named module. The study was performed using SUMO traffic simulator. A comparison is made between a fuzzy logic controller and a conventional fixed time controller. As a result, fuzzy logic controller has shown better performance. Taha Mahmood | Muzamil Eltejani Mohammed Ali | Akif Durdu ""A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Intersection Based on Real Data using SUMO Simulator"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23873.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/23873/a-two-stage-fuzzy-logic-adaptive-traffic-signal-control-for-an-isolated-intersection-based-on-real-data-using-sumo-simulator/taha-mahmood
DYNAMIC RESOURCE ALLOCATION IN ROAD TRANSPORT SECTOR USING MOBILE CLOUD COMPU...IAEME Publication
Literature review revealed application of various techniques for efficient use of existing resources in road transport sector vehicles, operators and related facilities. This issue assumes bigger dimensions in situations where there are multiple routes and the demand in the routes is highly fluctuating over the day. The application of the existing techniques as reported in literature addresses above issues to a considerable extent. However the main draw back in existing techniques is lack of
proper uninterrupted information about vehicles and demand available at a central place for allocation of vehicles in different roads and huge computational times required for processing. Cloud computing is a recently developed processing tool that is used in effective utilization of resources in transport sector under dynamic resource allocation.
CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATI...cscpconf
The intensive development of traffic engineering and technologies that are integrated into vehicles, roads and their surroundings, bring opportunities of real time transport mobility modeling. Based on such model it is then possible to establish a predictive layer that is capable of predicting short and long term traffic flow behavior. It is possible to create the real time model of traffic mobility based on generated data. However, data may have different geographical, temporal or other constraints, or failures. It is therefore appropriate to develop tools that artificially create missing data, which can then be assimilated with real data. This paper presents a mechanism describing strategies of generating artificial data using microsimulations. It describes traffic microsimulation based on our solution of multiagent framework over which a system for generating traffic data is built. The system generates data of a structure corresponding to the data acquired in the real world.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATI...csandit
The intensive development of traffic engineering and technologies that are integrated into
vehicles, roads and their surroundings, bring opportunities of real time transport mobility
modeling. Based on such model it is then possible to establish a predictive layer that is capable
of predicting short and long term traffic flow behavior. It is possible to create the real time
model of traffic mobility based on generated data. However, data may have different
geographical, temporal or other constraints, or failures. It is therefore appropriate to develop
tools that artificially create missing data, which can then be assimilated with real data. This
paper presents a mechanism describing strategies of generating artificial data using
microsimulations. It describes traffic microsimulation based on our solution of multiagent
framework over which a system for generating traffic data is built. The system generates data of
a structure corresponding to the data acquired in the real world.
Adaptive traffic lights based on traffic flow prediction using machine learni...IJECEIAES
Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbor regressor to predict traffic flow and reduce traffic congestion at intersections. We used the public roads dataset from the UK national road traffic to test our models. All machine learning algorithms obtained good performance metrics, indicating that they are valid for implementation in smart traffic light systems. Next, we implemented an adaptive traffic light system based on a random forest regressor model, which adjusts the timing of green and red lights depending on the road width, traffic density, types of vehicles, and expected traffic. Simulations of the proposed system show a 30.8% reduction in traffic congestion, thus justifying its effectiveness and the interest of deploying it to regulate the signaling problem in intersections.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Web performance prediction using geo statistical methodeSAT Journals
Abstract To provide Qos in distributed web systems, it is necessary to perform predicting in web systems. Then provide prediction technique on time and space of web resource downloaded using turning bands geostatistical simulation method. Web resources are obtained from a group of web servers worldwide by multi agent measurement systems which continuously monitor the web servers located in different geographical localization. The outcome of high-quality of Web performance calculation completed by resources of the Turning bands method, particularly in the situation when we place the Web servers were monitored by a Multi-agent Measurement Systems (MWING) localized in Poland. By means of satellite navigation system real life data like accident cases, first aid rescuers can accurately locate the place within certain specified range with maximum error control, so that the injured people can be saved as soon as possible. This method will save time or the areas in the outer part of the main zone. Keywords—Vibration sensor, Quality of Service, Networked Distributed System.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.