Kunjir et al., 2023 - Google Patents
Managing Smart Urban Transportation with the integration of Big Data Analytic PlatformKunjir et al., 2023
- Document ID
- 7838105260988327482
- Author
- Kunjir S
- Patil S
- Hingane B
- Pagariya J
- Rashid M
- Publication year
- Publication venue
- 2023 6th International Conference on Contemporary Computing and Informatics (IC3I)
External Links
Snippet
Urban traffic management is a major challenge for cities worldwide, but with the help of technology, such as big data analytics and intelligent transport systems, cities are working to improve their situations. An integrated big data analytics platform has the potential to change …
- 238000012517 data analytics 0 title abstract description 25
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yang et al. | Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems | |
Yuan et al. | A survey of traffic prediction: from spatio-temporal data to intelligent transportation | |
Du et al. | Deep irregular convolutional residual LSTM for urban traffic passenger flows prediction | |
Ding et al. | Towards generating network of bikeways from Mapillary data | |
Singh et al. | A novel framework to avoid traffic congestion and air pollution for sustainable development of smart cities | |
Zhu et al. | Inferring taxi status using gps trajectories | |
Qin et al. | A graph convolutional network model for evaluating potential congestion spots based on local urban built environments | |
Aschwanden et al. | Learning to walk: Modeling transportation mode choice distribution through neural networks | |
D'Alberto et al. | A sustainable smart mobility? Opportunities and challenges from a big data use perspective | |
Ma et al. | An overview of Hadoop applications in transportation big data | |
Srinivasarao et al. | Deep learning based condition monitoring of road traffic for enhanced transportation routing | |
Kunjir et al. | Managing Smart Urban Transportation with the integration of Big Data Analytic Platform | |
Xiong et al. | Identifying, Analyzing, and forecasting commuting patterns in urban public Transportation: A review | |
Sun et al. | Alleviating data sparsity problems in estimated time of arrival via auxiliary metric learning | |
Gupta et al. | Lstm based real-time smart parking system | |
Bishop | Decarbonising transport with intelligent mobility | |
Ghosh et al. | A machine learning approach to find the optimal routes through analysis of gps traces of mobile city traffic | |
AT&T | ||
Rahaman | Context-aware mobility analytics and trip planning | |
Sathyan | Traffic Flow Prediction using Machine Learning Techniques-A Systematic Literature Review | |
Sohn | AI-Based Transportation Planning and Operation | |
Dabiri | Application of deep learning in intelligent transportation systems | |
Gao et al. | iTA: Inferring Traffic Accident Hotspots with Vehicle Trajectories and Road Environment Data | |
Selod et al. | Big data in transportation | |
Jain et al. | Modern Technology for Evolving Mass Public Transportation in Cities |