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市场调查报告书
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1856851

废弃物物联网与人工智慧整合市场预测至2032年：按组件、废弃物类型、部署模式、技术、应用、最终用户和地区分類的全球分析

Internet of Waste & AI Integration Market Forecasts to 2032 - Global Analysis By Component (Hardware, Software and Services), Waste Type, Deployment Mode, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球废弃物互联网和人工智慧整合市场预计到 2025 年将达到 50.2 亿美元，到 2032 年将达到 177.9 亿美元，预测期内复合年增长率为 19.8%。

废弃物互联网（IoW）与人工智慧（AI）的融合正在将废弃物管理转变为一个更聪明和永续的系统。 IoW利用物联网连接的感测器和设备持续追踪废弃物的产生、分类和处置，而AI则处理这些数据，以优化收集计划、预测废弃物模式并提高回收效率。这种结合有助于降低成本、减少环境足迹并最大限度地提高材料回收率。透过提供精准的洞察，它使政府和组织能够实施有效的废弃物管理策略。简而言之，IoW与AI的合作正在推动更智慧、更环保、更有效率的废弃物管理方法的发展。

根据联合国环境规划署（环境署）发布的《全球废弃物管理展望》数据，每年产生的城市固态废弃物超过20亿吨，而数位化和人工智慧系统正日益被推荐用于优化收集、分类和回收。环境署倡导使用智慧垃圾桶、感测器网路和人工智慧驱动的路线规划，以减少对环境的影响并提高营运效率。

都市化和废弃物产生

快速的城市发展和不断增长的人口数量正显着推动着「废弃物联网」（IoW）与人工智慧（AI）整合市场的发展。城市扩张导致生活垃圾、废弃物和市政工业废弃物的数量不断增加，为垃圾的收集、分类和处置带来了挑战。将人工智慧与垃圾物联网结合，能够为即时监测和高效管理提供创新解决方案，废弃物环境影响和营运效率低下问题。物联网感测器提供持续数据，支援预测分析和简化废弃物收集流程。都市区对永续、经济高效且技术先进的废弃物管理解决方案的需求，正在推动智慧型系统的应用，使人工智慧主导的垃圾物联网成为有效处理现代城市废弃物的关键工具。

高昂的实施成本

高昂的实施成本阻碍了整合「废弃物联网」（IoW）和人工智慧（AI）的废弃物管理系统的普及。部署物联网基础设施，例如智慧垃圾桶、感测器和监控系统，需要大量的初始投资。而将人工智慧技术应用于预测分析、路线规划和自动化废弃物处理，则进一步增加了成本。小型企业和市政当局可能面临资金限制，难以采用这些先进解决方案。软体维护、升级和员工培训的持续成本也加重了财务负担。因此，基于「废弃物物联网」和人工智慧的系统所需的大量资金和营运成本，对市场构成了重大限制，尤其是在资金有限或规模较小的地区。

与可再生能源和循环经济的融合

人们日益关注循环经济原则和可再生能源，这为人工智慧驱动的「废弃物网路」（IoW）解决方案带来了广阔前景。透过物联网监控和人工智慧驱动的预测分析，废弃物能源化、堆肥和资源回收等技术可以变得更有效率。这些系统透过了解废弃物的类型和数量，优化回收流程、能源产出和材料再利用。市政当局和企业可以减少对掩埋的依赖，提高永续性，并从回收材料中获得收入。随着循环经济成为一项策略重点，整合人工智慧的「废弃物互联网」平台将在高效监控和管理废弃物方面发挥核心作用。这种协同效应将推动对环保废弃物管理技术的创新、合作和投资。

供应商之间竞争激烈

物联网和人工智慧整合市场正面临智慧废弃物管理解决方案供应商之间的激烈竞争。新兴企业和老牌公司的崛起造成了价格压力，降低了利润率，并增强了客户的议价能力。激烈的竞争要求企业不断创新以实现产品差异化；缺乏创新可能导致市场占有率的丧失。竞争对手之间的併购和联盟等策略性措施进一步加剧了市场挑战。无法适应快速发展的技术和竞争策略的公司将面临落后的风险。随着解决方案提供者数量的成长，在这种竞争环境下保持成长和客户忠诚度变得越来越困难。

新冠疫情的影响：

新冠疫情对「废弃物互联网」（IoW）和人工智慧整合市场产生了重大影响，既带来了挑战，也带来了机会。封锁措施扰乱了废弃物收集，延缓了智慧基础设施计划，供应链问题和资金限制也减缓了新技术的普及应用。同时，生物医学垃圾、医疗废弃物和生活废弃物的激增凸显了自动化、非接触式和智慧化废弃物管理系统的必要性。随着政府和市政当局寻求即时数据、预测工具和优化的收集策略以维护卫生和提高营运效率，人工智慧驱动的「废物网路」解决方案变得日益重要。疫情最终凸显了数位化和人工智慧驱动的废弃物解决方案在确保安全、永续和高效的废弃物管理方面发挥的关键作用。

预计在预测期内，云端基础的细分市场将占据最大份额。

由于其扩充性、易于适应性和低实施成本，预计在预测期内，云端基础方案将占据最大的市场份额。这些平台使政府和组织能够随时随地即时监控废弃物的产生、分类和处置，从而提高营运效率。它们还支援人工智慧主导的洞察、预测分析和自动化流程，而无需庞大的现场基础设施​​。云端解决方案可与物联网设备无缝集成，实现远端系统管理和持续软体更新，使其非常适合不断发展的城市环境。灵活性、便利性和低维护成本的结合，使云端部署成为该市场的首选方案。

预计在预测期内，市政和智慧城市领域将实现最高的复合年增长率。

预计在预测期内，市政和智慧城市领域将实现最高成长率。不断增长的城市人口、日益严重的环境问题以及对永续城市发展的追求，正促使城市管理部门采用人工智慧主导的物联网解决方案。这些技术能够实现预测性废弃物分析、优化收集路线、即时监控和流程自动化，从而降低成本并提高营运效率。智慧城市计画优先考虑绿色和以数据为中心的城市管理，这为人工智慧整合的废弃物系统提供了巨大的潜力。透过提高合规性、资源利用率和服务效率，在市政废弃物营运中采用智慧物联网解决方案，是推动此细分市场实现最高成长率的重要因素。

占比最大的地区：

预计北美将在预测期内占据最大的市场份额，这得益于其强大的技术基础设施、广泛的智慧城市项目以及支持永续废弃物管理的政府政策。该地区受益于先进的物联网连接、人工智慧技术以及以数据为中心的市政系统，从而提高了废弃物监测、分类和回收效率。健全的法律规范、日益增强的环保意识以及主要行业参与者的存在进一步巩固了北美市场的主导地位。北美许多城市正在采用人工智慧驱动的物联网平台，以提高效率、降低营运成本并促进环保废弃物处理。所有这些因素共同作用，使北美成为智慧废弃物管理解决方案市场份额最大的地区。

复合年增长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率。中国、印度和东南亚等国家快速的城市化进程、不断扩大的工业活动以及人口的成长，都催生了对高效能废弃物管理技术的强劲需求。各国政府致力于提升智慧城市和数位基础设施建设的倡议，正在加速人工智慧驱动的物联网平台的应用。日益增强的环保意识和支持永续废弃物处理实践的法规，进一步推动了市场扩张。由于对经济高效、扩充性且技术先进的解决方案有着极高的需求，亚太地区已成为成长最快的市场，这为供应商在人工智慧驱动的废弃物管理领域进行创新并巩固自身地位提供了绝佳机会。

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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究资讯来源
    • 初级研究资讯来源
    • 次级研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球废弃物互联网与人工智慧整合市场（按组件划分）

  • 硬体
  • 软体
  • 服务

6. 全球废弃物互联网与人工智慧整合市场（按废弃物类型划分）

  • 都市固态废弃物
  • 工业製程废弃物
  • 危险和废弃物废弃物
  • 电子废弃物（电子废弃物）
  • 医疗和废弃物废弃物

7. 全球废弃物互联网与人工智慧整合市场（按部署类型划分）

  • 云端基础的
  • 本地部署
  • 混合部署

8. 全球废弃物互联网与人工智慧整合市场（按技术划分）

  • 物联网基础设施
  • 人工智慧
  • 机器人与自动化
  • 云端运算和边缘运算

9. 全球废弃物互联网与人工智慧整合市场（按应用领域划分）

  • 智慧废弃物收集
  • 废弃物分类与回收
  • 掩埋监测
  • 路线优化
  • 排放追踪

第十章 全球废弃物互联网与人工智慧整合市场（按最终用户划分）

  • 地方政府和智慧城市
  • 工业设施
  • 商业企业
  • 住房部门
  • 废弃物管理公司

第十一章 全球废弃物互联网与人工智慧融合市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与併购
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十三章：企业概况

  • AI Superior
  • Greyparrot
  • Recycleye
  • EverestLabs
  • CleanRobotics
  • Big Belly Solar, LLC
  • Bine sp. z oo
  • Ecube Labs Co. Ltd.
  • AMP
  • Veolia
  • RTS
  • Bridgera
  • Rubicon Global
  • ZenRobotics
  • Waste Robotics
Product Code: SMRC31723

According to Stratistics MRC, the Global Internet of Waste & AI Integration Market is accounted for $5.02 billion in 2025 and is expected to reach $17.79 billion by 2032 growing at a CAGR of 19.8% during the forecast period. The fusion of the Internet of Waste (IoW) and Artificial Intelligence (AI) is transforming waste management into a more intelligent and sustainable system. IoW employs IoT-connected sensors and devices to track waste generation, sorting, and disposal continuously, while AI processes this data to streamline collection schedules, forecast waste patterns, and enhance recycling efficiency. This combination helps lower costs, reduce environmental footprint, and maximize material recovery. By delivering precise insights, it empowers governments and organizations to implement effective waste strategies. In essence, the collaboration between IoW and AI is driving the development of smarter, environmentally conscious, and resource-efficient waste management practices.

According to the United Nations Environment Programme (UNEP), data from its Global Waste Management Outlook shows that over 2 billion tonnes of municipal solid waste are generated annually, with digital and AI-based systems increasingly recommended to optimize collection, segregation, and recycling. UNEP advocates for smart bins, sensor networks, and AI-driven route planning to reduce environmental impact and improve operational efficiency.

Market Dynamics:

Driver:

Growing urbanization and waste generation

Rapid urban growth and rising population levels significantly drive the Internet of Waste (IoW) and AI market. Expanding cities generate increasing amounts of household, industrial, and municipal waste, which creates challenges for collection, sorting, and disposal. Integrating AI with IoW offers innovative solutions for real-time monitoring and efficient management, reducing environmental impact and operational inefficiencies. IoT sensors provide continuous data, enabling predictive analytics and streamlined waste collection. The demand for sustainable, cost-efficient, and technologically advanced waste management solutions in urban areas encourages the adoption of intelligent systems, establishing AI-driven IoW as a crucial tool for handling modern urban waste effectively.

Restraint:

High implementation costs

The adoption of Internet of Waste (IoW) and AI-integrated waste management systems is hindered by high implementation costs. Deploying IoT infrastructure, including smart bins, sensors, and monitoring systems, involves considerable initial investment. Incorporating AI technologies for predictive analysis, route planning, and automated waste handling further escalates expenses. Small-scale businesses and municipalities may struggle with financial limitations, limiting their ability to adopt these advanced solutions. Continuous costs for software maintenance, upgrades, and staff training add to the financial burden. Consequently, the substantial capital and operational requirements of IoW and AI-based systems act as a major market restraint, particularly in regions with limited funding or smaller operational scales.

Opportunity:

Integration with renewable energy and circular economy

The increasing focus on circular economy principles and renewable energy offers significant prospects for AI-enabled Internet of Waste (IoW) solutions. Technologies like waste-to-energy conversion, composting, and resource recovery gain efficiency through IoT monitoring and AI-powered predictive analysis. By understanding waste types and volumes, these systems optimize recycling processes, energy generation, and material reuse. Municipalities and industries can reduce landfill reliance, enhance sustainability, and create revenue streams from recovered resources. As the circular economy becomes a strategic priority, AI-integrated IoW platforms play a central role in monitoring and managing waste efficiently. This synergy encourages innovation, collaboration, and investment in environmentally responsible waste management technologies.

Threat:

Intense competition among vendors

The IoW and AI market is threatened by stiff competition among vendors offering intelligent waste management solutions. A growing number of startups and established firms create pricing pressures, diminish profit margins, and increase the bargaining power of clients. Intense rivalry requires continuous innovation to differentiate products; failure to innovate can lead to loss of market share. Strategic moves such as mergers, acquisitions, or partnerships among competitors further intensify market challenges. Companies unable to adapt to fast-evolving technologies and competitive strategies risk falling behind. As the number of solution providers grows, sustaining growth and customer loyalty becomes increasingly difficult in this highly competitive environment.

Covid-19 Impact:

The COVID-19 outbreak significantly influenced the AI-integrated Internet of Waste (IoW) market, creating both challenges and opportunities. Lockdowns disrupted waste collection, delayed smart infrastructure projects, and slowed the adoption of new technologies due to supply chain issues and financial limitations. Simultaneously, the surge in biomedical, medical, and household waste emphasized the need for automated, contactless, and intelligent waste management systems. AI-powered IoW solutions gained importance as governments and municipalities sought real-time data, predictive tools, and optimized collection strategies to maintain sanitation and operational efficiency. The pandemic ultimately highlighted the critical role of digital and AI-enabled waste solutions in ensuring safe, sustainable, and efficient waste management.

The cloud-based segment is expected to be the largest during the forecast period

The cloud-based segment is expected to account for the largest market share during the forecast period due to its ease of scalability, adaptability, and lower implementation costs. These platforms allow governments and organizations to monitor waste generation, segregation, and disposal in real-time from any location, enhancing operational efficiency. They also support AI-driven insights, predictive analytics, and automated processes without the need for extensive on-site infrastructure. Cloud solutions provide seamless integration with IoT devices, remote system management, and continuous software updates, making them highly practical for expanding urban environments. The combination of flexibility, convenience, and minimal maintenance makes cloud deployment the preferred choice in this market.

The municipalities & smart cities segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the municipalities & smart cities segment is predicted to witness the highest growth rate. Expanding urban populations, heightened environmental concerns, and the push for sustainable urban development are motivating city authorities to implement AI-driven IoW solutions. These technologies enable predictive waste analytics, optimized collection routes, real-time monitoring, and automated processes, reducing costs and improving operational efficiency. Smart city programs prioritize eco-friendly, data-centric urban management, offering significant prospects for AI-integrated waste systems. By enhancing compliance, resource utilization, and service efficiency, the adoption of intelligent IoW solutions in municipal waste operations positions this segment as the highest growth rate contributor in the market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its robust technological infrastructure, widespread smart city programs, and supportive governmental policies promoting sustainable waste management. The region benefits from advanced IoT connectivity, AI capabilities, and data-centric municipal systems that enhance waste monitoring, segregation, and recycling efficiency. Strong regulatory frameworks, growing environmental consciousness, and the presence of key industry players further strengthen its market dominance. Many North American cities are adopting AI-powered IoW platforms to improve efficiency, cut operational costs, and promote eco-friendly waste practices. Collectively, these factors establish North America as the region with the largest market share for intelligent waste management solutions.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapid urban growth, expanding industrial activities, and population increases in nations such as China, India, and Southeast Asia are creating strong demand for efficient waste management technologies. Government initiatives focusing on smart cities and enhanced digital infrastructure are accelerating the adoption of AI-powered IoW platforms. Rising environmental consciousness and supportive regulations for sustainable waste practices further drive market expansion. The region's need for cost-effective, scalable, and technologically advanced solutions makes it the fastest-growing market, offering significant opportunities for vendors to innovate and strengthen their presence in AI-enabled waste management.

Key players in the market

Some of the key players in Internet of Waste & AI Integration Market include AI Superior, Greyparrot, Recycleye, EverestLabs, CleanRobotics, Big Belly Solar, LLC, Bine sp. z o. o., Ecube Labs Co. Ltd., AMP, Veolia, RTS, Bridgera, Rubicon Global, ZenRobotics and Waste Robotics.

Key Developments:

In June 2025, Greyparrot has launched Deepnest: a world-first AI waste intelligence platform that gives brands direct access to their recyclable waste data. What happens to products when they become waste is a knowledge gap for most industries. This is due to limitations of waste infrastructure and a lack of available data. Deepnest plugs this knowledge gap, unlocking post-use packaging performance insights to help brands shape their products and business models.

In June 2024, Bigbelly Solar, LLC, a world leader in public space waste and recycling solutions for more than 20 years, marked the grand opening of its U.S. manufacturing facility. The facility, which straddles the communities of Methuen and Lawrence, is the primary production location for Bigbelly-branded bins, from budget-friendly to solar-powered smart waste options.

In October 2023, EverestLabs has announced that it is expanding globally with the opening of a new Robotics Operations Center office in Guntur, Andhra Pradesh, India. EverestLabs, developer of RecycleOS, an AI-enabled operating system for MRFs, expands into India which aligns with the company's commitment to support worldwide customers and is becoming a global powerhouse for engineering talent.

Components Covered:

  • Hardware
  • Software
  • Services

Waste Types Covered:

  • Municipal Solid Waste
  • Industrial Process Waste
  • Hazardous & Toxic Waste
  • Electronic Waste (E-waste)
  • Biomedical & Clinical Waste

Deployment Modes Covered:

  • Cloud-Based
  • On-Premise
  • Hybrid Deployments

Technologies Covered:

  • IoT Infrastructure
  • Artificial Intelligence
  • Robotics & Automation
  • Cloud & Edge Computing

Applications Covered:

  • Smart Waste Collection
  • Waste Sorting & Recycling
  • Landfill Monitoring
  • Route Optimization
  • Emission Tracking

End Users Covered:

  • Municipalities & Smart Cities
  • Industrial Facilities
  • Commercial Enterprises
  • Residential Sector
  • Waste Management Companies

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Internet of Waste & AI Integration Market, By Component

  • 5.1 Introduction
  • 5.2 Hardware
  • 5.3 Software
  • 5.4 Services

6 Global Internet of Waste & AI Integration Market, By Waste Type

  • 6.1 Introduction
  • 6.2 Municipal Solid Waste
  • 6.3 Industrial Process Waste
  • 6.4 Hazardous & Toxic Waste
  • 6.5 Electronic Waste (E-waste)
  • 6.6 Biomedical & Clinical Waste

7 Global Internet of Waste & AI Integration Market, By Deployment Mode

  • 7.1 Introduction
  • 7.2 Cloud-Based
  • 7.3 On-Premise
  • 7.4 Hybrid Deployments

8 Global Internet of Waste & AI Integration Market, By Technology

  • 8.1 Introduction
  • 8.2 IoT Infrastructure
  • 8.3 Artificial Intelligence
  • 8.4 Robotics & Automation
  • 8.5 Cloud & Edge Computing

9 Global Internet of Waste & AI Integration Market, By Application

  • 9.1 Introduction
  • 9.2 Smart Waste Collection
  • 9.3 Waste Sorting & Recycling
  • 9.4 Landfill Monitoring
  • 9.5 Route Optimization
  • 9.6 Emission Tracking

10 Global Internet of Waste & AI Integration Market, By End User

  • 10.1 Introduction
  • 10.2 Municipalities & Smart Cities
  • 10.3 Industrial Facilities
  • 10.4 Commercial Enterprises
  • 10.5 Residential Sector
  • 10.6 Waste Management Companies

11 Global Internet of Waste & AI Integration Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 AI Superior
  • 13.2 Greyparrot
  • 13.3 Recycleye
  • 13.4 EverestLabs
  • 13.5 CleanRobotics
  • 13.6 Big Belly Solar, LLC
  • 13.7 Bine sp. z o. o.
  • 13.8 Ecube Labs Co. Ltd.
  • 13.9 AMP
  • 13.10 Veolia
  • 13.11 RTS
  • 13.12 Bridgera
  • 13.13 Rubicon Global
  • 13.14 ZenRobotics
  • 13.15 Waste Robotics

List of Tables

  • Table 1 Global Internet of Waste & AI Integration Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Internet of Waste & AI Integration Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Internet of Waste & AI Integration Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global Internet of Waste & AI Integration Market Outlook, By Software (2024-2032) ($MN)
  • Table 5 Global Internet of Waste & AI Integration Market Outlook, By Services (2024-2032) ($MN)
  • Table 6 Global Internet of Waste & AI Integration Market Outlook, By Waste Type (2024-2032) ($MN)
  • Table 7 Global Internet of Waste & AI Integration Market Outlook, By Municipal Solid Waste (2024-2032) ($MN)
  • Table 8 Global Internet of Waste & AI Integration Market Outlook, By Industrial Process Waste (2024-2032) ($MN)
  • Table 9 Global Internet of Waste & AI Integration Market Outlook, By Hazardous & Toxic Waste (2024-2032) ($MN)
  • Table 10 Global Internet of Waste & AI Integration Market Outlook, By Electronic Waste (E-waste) (2024-2032) ($MN)
  • Table 11 Global Internet of Waste & AI Integration Market Outlook, By Biomedical & Clinical Waste (2024-2032) ($MN)
  • Table 12 Global Internet of Waste & AI Integration Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 13 Global Internet of Waste & AI Integration Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 14 Global Internet of Waste & AI Integration Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 15 Global Internet of Waste & AI Integration Market Outlook, By Hybrid Deployments (2024-2032) ($MN)
  • Table 16 Global Internet of Waste & AI Integration Market Outlook, By Technology (2024-2032) ($MN)
  • Table 17 Global Internet of Waste & AI Integration Market Outlook, By IoT Infrastructure (2024-2032) ($MN)
  • Table 18 Global Internet of Waste & AI Integration Market Outlook, By Artificial Intelligence (2024-2032) ($MN)
  • Table 19 Global Internet of Waste & AI Integration Market Outlook, By Robotics & Automation (2024-2032) ($MN)
  • Table 20 Global Internet of Waste & AI Integration Market Outlook, By Cloud & Edge Computing (2024-2032) ($MN)
  • Table 21 Global Internet of Waste & AI Integration Market Outlook, By Application (2024-2032) ($MN)
  • Table 22 Global Internet of Waste & AI Integration Market Outlook, By Smart Waste Collection (2024-2032) ($MN)
  • Table 23 Global Internet of Waste & AI Integration Market Outlook, By Waste Sorting & Recycling (2024-2032) ($MN)
  • Table 24 Global Internet of Waste & AI Integration Market Outlook, By Landfill Monitoring (2024-2032) ($MN)
  • Table 25 Global Internet of Waste & AI Integration Market Outlook, By Route Optimization (2024-2032) ($MN)
  • Table 26 Global Internet of Waste & AI Integration Market Outlook, By Emission Tracking (2024-2032) ($MN)
  • Table 27 Global Internet of Waste & AI Integration Market Outlook, By End User (2024-2032) ($MN)
  • Table 28 Global Internet of Waste & AI Integration Market Outlook, By Municipalities & Smart Cities (2024-2032) ($MN)
  • Table 29 Global Internet of Waste & AI Integration Market Outlook, By Industrial Facilities (2024-2032) ($MN)
  • Table 30 Global Internet of Waste & AI Integration Market Outlook, By Commercial Enterprises (2024-2032) ($MN)
  • Table 31 Global Internet of Waste & AI Integration Market Outlook, By Residential Sector (2024-2032) ($MN)
  • Table 32 Global Internet of Waste & AI Integration Market Outlook, By Waste Management Companies (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.