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Global Smart Waste Management Market to reach USD 7.89 billion by the end of 2030

Global Smart Waste Management Market Size Study & Forecast, by Waste Type (Solid Waste, Special Waste, E-Waste), By Method (Smart Collection, Smart Processing, Smart Disposal), By Source (Residential, Commercial, Industrial), and Regional Analysis, 2023-2030

Product Code: ICTICTI-17190239
Publish Date: 20-10-2023
Page: 200

Global Smart Waste Management Market is valued at approximately USD 2.56 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 15.1% over the forecast period 2023-2030. Smart waste management is a system that utilizes technology to create waste collection more competently, cost-effectivly, and environmentally friendly. It gathers information about garbage creation trends, behavior, and location using sensors, the Internet of Things (IoT), and data analytics. Waste collection routes, timetables, and disposal procedures are then optimized using this data. The increasing awareness of environmental sustainability, imposition of stringent waste management regulations, and high demand for real-time monitoring and optimization, coupled with the integration with smart city initiatives are the key factors that are driving the market demand across the globe.

The growing urbanization is a leading cause of waste generation that is putting a strain on traditional waste management systems. Smart waste management solutions can help to improve the efficiency of waste management in urban areas. According to World Bank in 2020, there were around 55% of the population that is approximately 4.2 billion inhabitants were recorded to live in urban areas. Furthermore, it is expected that the urban population is likely to continuously rise by 1.5 times and reached nearly 6 million by 2045. Consequentially, the rising need for effective waste collection, monitoring, and disposal drives the adoption of smart waste management technologies. Moreover, the rising technological advancements related to smart waste management solutions, as well as increased focus on recycling and circular economy creates numerous lucrative opportunities over the anticipated period. However, the high costs of implementation and the lack of efficient connectivity are challenging the market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Smart Waste Management Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the stringent regulations regarding waste management, rising emphasis on reducing carbon emissions, and the presence of key market players. Whereas, Asia Pacific is expected to grow at the highest CAGR over the forecasting years. Increasing environmental concerns, the rapid development of residential projects such as smart cities, along with the rising focus on recycling and circular economy are significantly propelling the market demand across the region.

Major market players included in this report are:
Ecube Labs Co Ltd
Waste Management Inc
Republic Services Inc
Sensoneo j. s. a.
Covanta Holding Corporation
Bigbelly, Inc.
Veolia Environnement S.A
SUEZ Environmental Services S.A.
Enevo Oy

Recent Developments in the Market:
Ø In October 2022, Covanta, a provider of environmental services for businesses and communities across North America acquired Biologic- a California-based environmental management company offering full waste management services. Covanta has completed a series of acquisitions by the EQT Infrastructure V fund, and this initiative is has focused on strengthening the company’s geographic footprints across the California markets.

Global Smart Waste Management Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Waste Type, Method, Source, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

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 years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential 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:

By Waste Type:
Solid Waste
Special Waste

By Method:
Smart Collection
Smart Processing
Smart Disposal

By Source:

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Smart Waste Management Market, by Region, 2020-2030 (USD Billion)
1.2.2. Smart Waste Management Market, by Waste Type, 2020-2030 (USD Billion)
1.2.3. Smart Waste Management Market, by Method, 2020-2030 (USD Billion)
1.2.4. Smart Waste Management Market, by Source, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Smart Waste Management Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Smart Waste Management Market Dynamics
3.1. Smart Waste Management Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing Awareness of environmental sustainability Rising waste generation and Urbanization
3.1.2. Market Challenges High costs of implementation Lack of efficient connectivity
3.1.3. Market Opportunities Growing technological advancements related to smart waste management solutions Increased focus on recycling and circular economy
Chapter 4. Global Smart Waste Management Market Industry 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
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Smart Waste Management Market, by Waste Type
5.1. Market Snapshot
5.2. Global Smart Waste Management Market by Waste Type, Performance – Potential Analysis
5.3. Global Smart Waste Management Market Estimates & Forecasts by Waste Type 2020-2030 (USD Billion)
5.4. Smart Waste Management Market, Sub Segment Analysis
5.4.1. Solid Waste
5.4.2. Special Waste
5.4.3. E-Waste
Chapter 6. Global Smart Waste Management Market, by Method
6.1. Market Snapshot
6.2. Global Smart Waste Management Market by Method, Performance – Potential Analysis
6.3. Global Smart Waste Management Market Estimates & Forecasts by Method 2020-2030 (USD Billion)
6.4. Smart Waste Management Market, Sub Segment Analysis
6.4.1. Smart Collection
6.4.2. Smart Processing
6.4.3. Smart Disposal
Chapter 7. Global Smart Waste Management Market, by Source
7.1. Market Snapshot
7.2. Global Smart Waste Management Market by Source, Performance – Potential Analysis
7.3. Global Smart Waste Management Market Estimates & Forecasts by Source 2020-2030 (USD Billion)
7.4. Smart Waste Management Market, Sub Segment Analysis
7.4.1. Residential
7.4.2. Commercial
7.4.3. Industrial
Chapter 8. Global Smart Waste Management Market, Regional Analysis
8.1. Top Leading Countries
8.2. Top Emerging Countries
8.3. Smart Waste Management Market, Regional Market Snapshot
8.4. North America Smart Waste Management Market
8.4.1. U.S. Smart Waste Management Market Waste Type breakdown estimates & forecasts, 2020-2030 Method breakdown estimates & forecasts, 2020-2030 Source breakdown estimates & forecasts, 2020-2030
8.4.2. Canada Smart Waste Management Market
8.5. Europe Smart Waste Management Market Snapshot
8.5.1. U.K. Smart Waste Management Market
8.5.2. Germany Smart Waste Management Market
8.5.3. France Smart Waste Management Market
8.5.4. Spain Smart Waste Management Market
8.5.5. Italy Smart Waste Management Market
8.5.6. Rest of Europe Smart Waste Management Market
8.6. Asia-Pacific Smart Waste Management Market Snapshot
8.6.1. China Smart Waste Management Market
8.6.2. India Smart Waste Management Market
8.6.3. Japan Smart Waste Management Market
8.6.4. Australia Smart Waste Management Market
8.6.5. South Korea Smart Waste Management Market
8.6.6. Rest of Asia Pacific Smart Waste Management Market
8.7. Latin America Smart Waste Management Market Snapshot
8.7.1. Brazil Smart Waste Management Market
8.7.2. Mexico Smart Waste Management Market
8.8. Middle East & Africa Smart Waste Management Market
8.8.1. Saudi Arabia Smart Waste Management Market
8.8.2. South Africa Smart Waste Management Market
8.8.3. Rest of Middle East & Africa Smart Waste Management Market

Chapter 9. Competitive Intelligence
9.1. Key Company SWOT Analysis
9.1.1. Company 1
9.1.2. Company 2
9.1.3. Company 3
9.2. Top Market Strategies
9.3. Company Profiles
9.3.1. Ecube Labs Co Ltd Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
9.3.2. Waste Management Inc
9.3.3. Republic Services Inc
9.3.4. Sensoneo j. s. a.
9.3.5. Covanta Holding Corporation
9.3.6. Bigbelly, Inc.
9.3.7. Veolia Environnement S.A
9.3.8. SUEZ Environmental Services.
9.3.9. Enevo Oy
9.3.10. Urbiotica
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. 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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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.
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