INFORMATION & COMMUNICATION TECHNOLOGY
Global Smart Parking Market - Industry Trends and Forecast to 2032
REPORT OVERVIEW
Global Smart Parking Market, By System Type (Guided Park Assist, Smart Park Assist, On-Street and Off-Street), Component (Hardware, Software and Services), Sensor Technology (Ultrasonic Sensor, Radar Sensor, and Image Sensor), Vertical (Government, Commercial, and Corporate), Application (Security and Surveillance, Smart Payment Systems, E-parking, and License Plate Recognition), Region (North America, Europe, Asia-Pacific, South America, Middle East and Africa) – Industry Trends and Forecast to 2032.
Market Insights
The global Smart Parking market size is valued to be USD xx million in 2023 and is expected to reach USD xx million by 2032, and it is expected to register a CAGR of xx% over the forecast period 2024-2032.
Smart parking is the application of new technology to increase the efficiency and convenience of parking spots. This often entails integrating sensors, cameras, and data analytics to monitor parking availability in real time, direct cars to available places, and optimize parking space use. Smart parking systems use automation and intelligent management to minimize traffic congestion, lower car emissions, and improve the entire parking experience for both drivers and operators.
The respective global report analyses market trends, consumer behaviour and industry dynamics to guide towards entry into new markets with ease. Also, it assists in tailoring market specific and related products and services to meet the needs, preferences, and expectations of target audience by delving into their psychology. The report also specializes with comprehensive and extensive competitive analysis which offers useful insights into competitor strengths, weaknesses, opportunities, and threats. The respective report offers exclusive insights into the potential impact of disruptive developments and technologies that are expected to completely transform corporate operations. The context includes tailor-made research solutions to create a stronger footprint in their particular industries thereby offering dedicated customized solutions according to the client needs which helps in addressing unique business challenges with more simplified and efficient decision-making solutions.
Market Dynamics
DRIVERS
- Rapid urbanization
- Growing vehicle ownership
RESTRAINTS
- High initial investment
- Complexity of integration
OPPORTUNITIES
- Smart city initiatives
- Technological advancements
CHALLENGES
- Privacy and data security concerns
- Lack of standardization
SEGMENTATION
- System Type
- Guided Park Assist
- Smart Park Assist
- On-Street
- Off-Street
- Garage Parking
- Lot Parking
- Component
- Hardware
- Sensors
- Cameras
- Parking Meters
- Digital Guidance Signage
- Others
- Software
- Parking Management Platforms
- SDK/API
- Services
- Consulting
- Integration and Support Services
- Device Management Services
- Sensor Technology
- Ultrasonic Sensor
- Radar Sensor
- Image Sensor
- Vertical
- Government
- Commercial
- Corporate
- Application
- Security and Surveillance
- Smart Payment Systems
- E-parking
- License Plate Recognition
The respective global report is completely customizable specific to regions (North America, Europe, Asia-Pacific, South America, Middle East and Africa), countries, and segments as per the client requirements.
REGIONAL SEGMENTATION
- North America
- U.S.
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Russia
- The Netherlands
- Belgium
- Turkey
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Malaysia
- Australia
- Thailand
- Philippines
- Rest of Asia-Pacific
- South America
- Brazil
- Argentina
- Chile
- Colombia
- Rest of South America
- Middle East and Africa
- Kingdom of Saudi Arabia
- South Africa
- U.A.E.
- Egypt
- Rest of Middle East and Africa
KEY MARKET PLAYERS
- Siemens AG
- Robert Bosch GmbH
- Continental AG
- Valeo
- AISIN SEIKI Co. Ltd.
- Amano Corporation
- AppyWay
- Smart Parking
- Klaus Multiparking
- TKH Security B.V.
Table OF CONTENTS
- SECTION 1 - INTRODUCTION
- 1.1 Taxonomy
- 1.2 Market Overview
- 1.3 Currency and Limitations
- 1.3.1 Currency
- 1.3.2 Limitations
- 1.4 Key Competitors
- SECTION 2 - RESEARCH METHODOLOGY
- 2.1 Research Approach
- 2.2 Data Collection and Validation
- 2.2.1 Secondary Research
- 2.2.2 Primary Research
- 2.3 Market Assessment
- 2.3.1 Market Size Estimation
- 2.3.2 Bottom-up Approach
- 2.3.3 Top-down Approach
- 2.3.4 Growth Forecast
- 2.4 Market Study Assumptions
- 2.5 Data Sources
- SECTION 3 - EXECUTIVE SUMMARY
- 3.1 Global Smart Parking Market, by System Type
- 3.2 Global Smart Parking Market, by Component
- 3.3 Global Smart Parking Market, by Sensor Technology
- 3.4 Global Smart Parking Market, by Vertical
- 3.5 Global Smart Parking Market, by Application
- 3.6 Global Smart Parking Market, by Geography
- 3.7 Market Position Grid
- SECTION 4 - PREMIUM INSIGHTS
- 4.1 Regulatory Framework
- 4.1.1 Standards
- 4.1.2 Regulatory Landscape
- 4.2 Value Chain Analysis
- 4.3 Supply Chain Analysis
- 4.4 COVID-19 Impact
- 4.5 Russia-Ukraine War Impact
- 4.6 PORTER's Five Force Analysis
- 4.7 PESTLE Analysis
- 4.8 SWOT Analysis
- 4.9 Go to Market Strategy
- 4.10 Opportunity Orbit
- 4.11 Multivariate Modelling
- 4.12 Pricing Analysis
- SECTION 5 - MARKET DYNAMICS
- 5.1 Trends
- 5.1.1 Enhanced customer experience
- 5.1.2 Mobile applications and digital platforms
- 5.1.3 Trend 3
- 5.2 Drivers
- 5.2.1 Rapid urbanization
- 5.2.2 Growing vehicle ownership
- 5.2.3 Driver 3
- 5.2.4 Driver 4
- 5.3 Restraints
- 5.3.1 High initial investment
- 5.3.2 Complexity of integration
- 5.3.3 Restraint 3
- 5.4 Opportunities
- 5.4.1 Smart city initiatives
- 5.4.2 Technological advancements
- 5.4.3 Opportunity 3
- 5.4.4 Opportunity 4
- 5.5 Challenges
- 5.5.1 Privacy and data security concerns
- 5.5.2 Lack of standardization
- 5.5.3 Challenge 3
- SECTION 6 - GLOBAL SMART PARKING MARKET, BY SYSTEM TYPE
- 6.1 System Type Summary
- 6.2 Market Attractive Index
- 6.3 Global Smart Parking Market, by System Type (2019-2032)
- SECTION 7 - GLOBAL SMART PARKING MARKET, BY COMPONENT
- 7.1 Component Summary
- 7.2 Market Attractive Index
- 7.3 Global Smart Parking Market, by Component (2019-2032)
- SECTION 8 - GLOBAL SMART PARKING MARKET, BY SENSOR TECHNOLOGY
- 8.1 Sensor Technology Summary
- 8.2 Market Attractive Index
- 8.3 Global Smart Parking Market, by Sensor Technology (2019-2032)
- SECTION 9 - GLOBAL SMART PARKING MARKET, BY VERTICAL
- 9.1 Vertical Summary
- 9.2 Market Attractive Index
- 9.3 Global Smart Parking Market, by Vertical (2019-2032)
- SECTION 10 - GLOBAL SMART PARKING MARKET, BY APPLICATION
- 10.1 Application Summary
- 10.2 Market Attractive Index
- 10.3 Global Smart Parking Market, by Application (2019-2032)
- SECTION 11 - GLOBAL SMART PARKING MARKET, BY GEOGRAPHY
- 11.1 Regional Summary
- 11.2 Market Attractive Index
- 11.3 Global Smart Parking Market, by Geography (2019-2032)
- SECTION 12 - NORTH AMERICA SMART PARKING MARKET
- 12.1 North America Summary
- 12.2 Market Attractive Index
- 12.3 North America Smart Parking Market, by System Type (2019-2032)
- 12.4 North America Smart Parking Market, by Component (2019-2032)
- 12.5 North America Smart Parking Market, by Sensor Technology (2019-2032)
- 12.6 North America Smart Parking Market, by Vertical (2019-2032)
- 12.7 North America Smart Parking Market, by Application (2019-2032)
- 12.8 North America Smart Parking Market, by Country (2019-2032)
- 12.8.1 U.S.
- 12.8.2 Canada
- 12.8.3 Mexico
- 12.8.4 Rest of North America
- SECTION 13 - EUROPE SMART PARKING MARKET
- 13.1 Europe Summary
- 13.2 Market Attractive Index
- 13.3 Europe Smart Parking Market, by System Type (2019-2032)
- 13.4 Europe Smart Parking Market, by Component (2019-2032)
- 13.5 Europe Smart Parking Market, by Sensor Technology (2019-2032)
- 13.6 Europe Smart Parking Market, by Vertical (2019-2032)
- 13.7 Europe Smart Parking Market, by Application (2019-2032)
- 13.8 Europe Smart Parking Market, by Country (2019-2032)
- 13.8.1 Germany
- 13.8.2 U.K.
- 13.8.3 France
- 13.8.4 Italy
- 13.8.5 Spain
- 13.8.6 Russia
- 13.8.7 The Netherlands
- 13.8.8 Belgium
- 13.8.9 Turkey
- 13.8.10 Rest of Europe
- SECTION 14 - ASIA-PACIFIC SMART PARKING MARKET
- 14.1 Asia-Pacific Summary
- 14.2 Market Attractive Index
- 14.3 Asia-Pacific Smart Parking Market, by System Type (2019-2032)
- 14.4 Asia-Pacific Smart Parking Market, by Component (2019-2032)
- 14.5 Asia-Pacific Smart Parking Market, by Sensor Technology (2019-2032)
- 14.6 Asia-Pacific Smart Parking Market, by Vertical (2019-2032)
- 14.7 Asia-Pacific Smart Parking Market, by Application (2019-2032)
- 14.8 Asia-Pacific Smart Parking Market, by Country (2019-2032)
- 14.8.1 China
- 14.8.2 India
- 14.8.3 Japan
- 14.8.4 South Korea
- 14.8.5 Singapore
- 14.8.6 Malaysia
- 14.8.7 Australia
- 14.8.8 Thailand
- 14.8.9 Philippines
- 14.8.10 Rest of Asia-Pacific
- SECTION 15 - SOUTH AMERICA SMART PARKING MARKET
- 15.1 South America Summary
- 15.2 Market Attractive Index
- 15.3 South America Smart Parking Market, by System Type (2019-2032)
- 15.4 South America Smart Parking Market, by Component (2019-2032)
- 15.5 South America Smart Parking Market, by Sensor Technology (2019-2032)
- 15.6 South America Smart Parking Market, by Vertical (2019-2032)
- 15.7 South America Smart Parking Market, by Application (2019-2032)
- 15.8 South America Smart Parking Market, by Country (2019-2032)
- 15.8.1 Brazil
- 15.8.2 Argentina
- 15.8.3 Chile
- 15.8.4 Colombia
- 15.8.5 Rest of South America
- SECTION 16 - MIDDLE EAST AND AFRICA SMART PARKING MARKET
- 16.1 Middle East and Africa Summary
- 16.2 Market Attractive Index
- 16.3 Middle East and Africa Smart Parking Market, by System Type (2019-2032)
- 16.4 Middle East and Africa Smart Parking Market, by Component (2019-2032)
- 16.5 Middle East and Africa Smart Parking Market, by Sensor Technology (2019-2032)
- 16.6 Middle East and Africa Smart Parking Market, by Vertical (2019-2032)
- 16.7 Middle East and Africa Smart Parking Market, by Application (2019-2032)
- 16.8 Middle East and Africa Smart Parking Market, by Country (2019-2032)
- 16.8.1 Kingdom of Saudi Arabia
- 16.8.2 South Africa
- 16.8.3 U.A.E.
- 16.8.4 Egypt
- 16.8.5 Rest of Middle East and Africa
- SECTION 17 - COMPANY SHARE ANALYSIS
- 17.1 Global Smart Parking Market, Company Share Analysis
- 17.2 North America Smart Parking Market, Company Share Analysis
- 17.3 Europe Smart Parking Market, Company Share Analysis
- 17.4 Asia-Pacific Smart Parking Market, Company Share Analysis
- SECTION 18 - COMPANY PROFILES
- 18.1 Siemens AG
- 18.1.1 Company Snapshot
- 18.1.2 Financial Overview
- 18.1.3 Product Portfolio
- 18.1.4 Recent Developments
- 18.2 Robert Bosch GmbH
- 18.2.1 Company Snapshot
- 18.2.2 Financial Overview
- 18.2.3 Product Portfolio
- 18.2.4 Recent Developments
- 18.3 Continental AG
- 18.3.1 Company Snapshot
- 18.3.2 Financial Overview
- 18.3.3 Product Portfolio
- 18.3.4 Recent Developments
- 18.4 Valeo
- 18.4.1 Company Snapshot
- 18.4.2 Financial Overview
- 18.4.3 Product Portfolio
- 18.4.4 Recent Developments
- 18.5 AISIN SEIKI Co. Ltd.
- 18.5.1 Company Snapshot
- 18.5.2 Financial Overview
- 18.5.3 Product Portfolio
- 18.5.4 Recent Developments
- 18.6 Amano Corporation
- 18.6.1 Company Snapshot
- 18.6.2 Financial Overview
- 18.6.3 Product Portfolio
- 18.6.4 Recent Developments
- 18.7 AppyWay
- 18.7.1 Company Snapshot
- 18.7.2 Financial Overview
- 18.7.3 Product Portfolio
- 18.7.4 Recent Developments
- 18.8 Smart Parking
- 18.8.1 Company Snapshot
- 18.8.2 Financial Overview
- 18.8.3 Product Portfolio
- 18.8.4 Recent Developments
- 18.9 Klaus Multiparking
- 18.9.1 Company Snapshot
- 18.9.2 Financial Overview
- 18.9.3 Product Portfolio
- 18.9.4 Recent Developments
- 18.10 TKH Security B.V.
- 18.10.1 Company Snapshot
- 18.10.2 Financial Overview
- 18.10.3 Product Portfolio
- 18.10.4 Recent Developments
- SECTION 19 - RELATED REPORTS
- SECTION 20 - DISCLAIMER
RESEARCH METHODOLOGY
The research methodology employed in Uniprism Market Research involves four basic steps namely research and data collection, data pre-processing, modeling and forecasting, quality assurance and output.
RESEARCH AND DATA COLLECTION
A tripod model research technique is followed for research and data collection in which various approaches such as primary research, secondary research, and product mapping are considered.
Primary research basically involves the process of conducting personalized interviews with market related professionals of major market players, investors, distributors, vendors and many more.
The secondary research include data published by government, annual reports, press releases, investor presentations of companies, white papers, certified publications, annual manufacturing limit of the respective industries related to the market, production consumption analysis of certain products respective to the market and many more.
Below mention are few of the sources which we have considered while estimating the market size:
For instance,
- Research articles published on Technium
- Science and MDPI
- Research publications by government approved associations and societies
Product mapping means the process of mapping the list of products that a key player contributes to the market as well as estimating the revenue of those products in order to define the Global Company share analysis of the respective Global Company in global, regional, and country level markets.
DATA PRE-PROCESSING
The term "data pre-processing" refers to the collection of procedures and methods used to clean, modify, and make ready for analysis the raw data gathered during research and data collection. The completion of this phase is necessary to guarantee that the data are reliable, consistent, and appropriate for statistical analysis and other data-driven tasks. The data pre-processing ensures that the information gathered from research and data collection is comparable and expressed in standard units, by the integration of missing data pointers and algorithmic approaches.
MODELING AND FORECASTING
The process of developing mathematical, statistical, or computational representations of real-world occurrences or relationships is known as modelling. These models are intended to replicate and explain market interactions, interdependence, and dynamics. These models are used by Uniprism Market Research to acquire a better knowledge of numerous market characteristics such as customer preferences, pricing elasticity, competition dynamics, and more. Depending on the individual study aims, many types of models are utilized, such as regression models, econometric models, decision tree models, and machine learning models.
Forecasting is the process of predicting future market conditions, trends, and occurrences using past data and models. Forecasting is used by Uniprism Market Research to estimate future sales, demand for products or services, market growth, and other important performance metrics. Forecasting accurately can assist organizations in making educated decisions about resource allocation, pricing, inventory management, and marketing tactics.
We create standardized bottom-up or top-down models that scale by leveraging data science and machine learning technology. All our market models consider the unique market characteristics of each country. Forecasting is based on major market indicators and a combination of traditional methodologies, such as exponential smoothing, time series analysis, regression analysis, and more modern techniques such as machine learning algorithms are all forecasting methodologies. The method chosen is determined on the nature of the data and the specific forecasting aims.
QUALITY ASSURANCE AND OUTPUT
Quality assurance and output involves the process of validation, adjustments, further publications of key market indicators. Extensive plausibility and consistency tests are performed on derived time series to ensure the high degree of quality of our market analysis. This quality assurance procedure also includes rigorous inspection, validation, and editing by an experienced management team to assure the dependability of the published data.