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Global Connected Rail Market to reach xx by 2028.

Global Connected Rail Market Size study, byService (Passenger Mobility, PIS, Train Tracking & Monitoring, Automated Fare Collection, Predictive maintenance, Freight Management), by Rolling Stock (Diesel Locomotive, Electric Locomotive, DMU, EMU, Light Rail/Tram Car, Subway/Metro Vehicle, Passenger Coach, Freight Wagon, Rail Signaling System (PTC, CBTC & ATC),and Regional Forecasts 2022-2028

Product Code: ALTST-79385192
Publish Date: 23-05-2022
Page: 200

Global Connected Rail Market is valued approximately XX in 2021 and is anticipated to grow with a healthy growth rate of more than xx% over the forecast period 2022-2028. The connected rail solution is useful for monetizing high speed Internet on a moving train, where data and transactions are handled via a Wi-Fi platform. It has several advantages, including allowing customers to work while travelling, which can be viewed as a significant instrument for increasing passenger rates and client happiness.The constant demand for safety and security in railways, commuter comfort, government support, growing economy, and increasing population are the primary drivers driving the expansion of the rail systems and services industry. Continuous advancements in data management application and advanced analytics promise to transform the railway industry and commuter experience. Connected technology aids in the improvement of safety, train control, traffic management, and visual automated monitoring on trains and platforms.Rising passenger traffic is predicted to increase data usage, which would drive demand for linked rail markets. The growing adoption of IoT (Internet of Things) is expected to create a significant potential for the connected rail sector.Technology companies are collaborating with telecommunications companies to improve network connectivity. IoT in railways represents a business opportunity for a variety of digital railway solution and telecommunication technology providers.Siemens and VGF collaborated to create the Digital Train Control System in December 2021. v This technology is planned to replace the traditional train control system now in use in metro and tram networks. This technology is being developed in order to boost the capacity and efficiency of railway lines, particularly in underground parts.Robert Bosch GmbH debuted an advanced driver assistance system for city rail transit in November 2021. In the case of a potential accident, it initially alerts the tram driver with a signal. If the driver does not intervene, or intervenes too late, the system automatically brakes the tram until it comes to a complete stop, preventing or at least reducing the collision as much as possible.

The key regions considered for the global Connected Rail Marketstudy includes Asia Pacific, North America, Europe, Latin America, and Rest of the World.North America’s transportation system is diverse, with a large transcontinental rail network. In North America, the increased adoption of advanced technologies has resulted in the development of smart cities and smart transportation projects. As a result, the market for connected rail will expand in the future. Wherreas, Asia Pacific is home to developing economies such as China, Japan, South Korea, and India. The region’s linked rail business is increasing as a result of urbanisation, increased investments in digital transformation, rising GDP in nations such as China and India, and investments in freight train infrastructure to are responsible for Connected Rail Market growth in the region.

Major market player included in this report are:
Wabtec Corporation
Robert Bosch Gmbh
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
Passenger Mobility and Services
Passenger Information System
Train Tracking & Monitoring Solutions
Automated Fare Collection System
IP Video Surveillance
Predictive Maintenance
Freight Management System

By Rolling Stock:

Diesel Locomotive
Electric Locomotive
Light Rail/Tram Car
Subway/Metro Vehicle
Passenger Coach
Freight Wagon

By Safety & Signalling System:

Positive Train Control (PTC)
Communication/Computer-based Train Control (CBTC)
Automated/Integrated Train Control (ATC)

By Region:
North America

Asia Pacific
South Korea
Latin America
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Connected Rail Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. Connected Rail Market, by Region, 2020-2028 (USD Billion)
1.2.2. Connected Rail Market, by Service,2020-2028 (USD Billion)
1.2.3. Connected Rail Market, by Rolling Stock,2020-2028 (USD Billion)
1.2.4. Connected Rail Market, by Safety & Signalling System,2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Connected Rail Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Connected Rail Market Dynamics
3.1. Connected Rail Market Impact Analysis (2020-2028)
3.1.1. Market Drivers Deployment of Internet of Things in railways Increasing emphasis on smart infrastructure
3.1.2. Market Challenges Data and privacy security of commuters
3.1.3. Market Opportunities Autonomous train represents significant opportunity for connected rail Market
Chapter 4. Global Connected Rail MarketIndustry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Connected Rail Market, by Service
6.1. Market Snapshot
6.2. Global Connected Rail Market by Service, Performance – Potential Analysis
6.3. Global Connected Rail Market Estimates & Forecasts by Service2018-2028 (USD Billion)
6.4. Connected Rail Market, Sub Segment Analysis
6.4.1. Passenger Mobility and Services
6.4.2. Passenger Information System
6.4.3. Train Tracking & Monitoring Solutions
6.4.4. Automated Fare Collection System
6.4.5. IP Video Surveillance
6.4.6. Predictive Maintenance
6.4.7. Freight Management System
6.4.8. Others
Chapter 7. Global Connected Rail Market, by Rolling Stock
7.1. Market Snapshot
7.2. Global Connected Rail Market by Rolling Stock, Performance – Potential Analysis
7.3. Global Connected Rail Market Estimates & Forecasts by Rolling Stock2018-2028 (USD Billion)
7.4. Connected Rail Market, Sub Segment Analysis
7.4.1. Diesel Locomotive
7.4.2. Electric Locomotive
7.4.3. DMU
7.4.4. EMU
7.4.5. Light Rail/Tram Car
7.4.6. Subway/Metro Vehicle
7.4.7. Passenger Coach
7.4.8. Freight Wagon
Chapter 8. Global Connected Rail Market, by Safety & Signalling System
8.1. Market Snapshot
8.2. Global Connected Rail Market by Safety & Signalling System, Performance – Potential Analysis
8.3. Global Connected Rail Market Estimates & Forecasts by Safety & Signalling System2018-2028 (USD Billion)
8.4. Connected Rail Market, Sub Segment Analysis
8.4.1. Positive Train Control (PTC)
8.4.2. Communication/Computer-based Train Control (CBTC)
8.4.3. Automated/Integrated Train Control (ATC)
Chapter 9. Global Connected Rail Market, Regional Analysis
9.1. Connected Rail Market, Regional Market Snapshot
9.2. North America Connected Rail Market
9.2.1. U.S.Connected Rail Market Servicebreakdown estimates & forecasts, 2018-2028 Rolling Stockbreakdown estimates & forecasts, 2018-2028 Safety & Signalling Systembreakdown estimates & forecasts, 2018-2028
9.2.2. CanadaConnected Rail Market
9.3. Europe Connected Rail Market Snapshot
9.3.1. U.K. Connected Rail Market
9.3.2. Germany Connected Rail Market
9.3.3. France Connected Rail Market
9.3.4. Spain Connected Rail Market
9.3.5. Italy Connected Rail Market
9.3.6. Rest of EuropeConnected Rail Market
9.4. Asia-PacificConnected Rail Market Snapshot
9.4.1. China Connected Rail Market
9.4.2. India Connected Rail Market
9.4.3. JapanConnected Rail Market
9.4.4. Australia Connected Rail Market
9.4.5. South Korea Connected Rail Market
9.4.6. Rest of Asia PacificConnected Rail Market
9.5. Latin America Connected Rail Market Snapshot
9.5.1. Brazil Connected Rail Market
9.5.2. Mexico Connected Rail Market
9.6. Rest of The World Connected Rail Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles SiemensKey Information Overview Financial (Subject to Data Availability) Rolling StockSummary Recent Developments
10.2.2. Hitachi
10.2.3. Wabtec Corporation
10.2.4. Trimble
10.2.5. Robert Bosch Gmbh
10.2.6. Huawei
10.2.7. Cisco
10.2.8. Nokia
10.2.9. Atos
10.2.10. IBM
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
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