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市场调查报告书

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1490922

群体智慧市场规模- 按模型（蚁群优化、粒子群优化）、按功能（优化、集群、调度、路由）、按应用（机器人、无人机、人类集群）、按最终用户和预测，2024 - 2032 年

Swarm Intelligence Market Size - By Model (Ant Colony Optimization, Particle Swarm Optimization), By Capability (Optimization, Clustering, Scheduling, Routing), By Application (Robotics, Drones, Human Swarming), By End Users & Forecast, 2024 - 2032

出版日期: 2024年03月22日 | 出版商:

Global Market Insights Inc. | 英文 240 Pages | 商品交期: 2-3个工作天内

价格

简介目录

预计从 2024 年到 2032 年，群体智慧市场规模将以超过 38.5% 的复合年增长率成长。群体智慧演算法透过模仿自然群体中观察到的集体行为来提供有效的问题解决能力。此外，人工智慧（AI）和机器学习（ML）技术的进步正在增强群体智慧系统的效能和可扩展性。

自动驾驶汽车、机器人和优化任务的日益普及也增加了市场吸引力。政府和私人组织不断增加的合作研究工作和投资正在进一步促进群体智慧解决方案的开发和商业化。例如，2024 年4 月，微软推出了Phi-3-mini，这是其第一个小语言模型(SLM)，旨在透过具有成本效益的人工智慧选项扩大其客户群，同时重申其对变革性科技以彻底改变工作和社会的承诺。

整个产业分为模型、能力、应用、最终用户和区域。

根据模型，由于演算法的简单性、效率和可扩展性，粒子群优化 (PSO) 领域的群体智慧市场将在 2024 年至 2032 年间以稳健的复合年增长率扩展。 PSO 演算法透过模拟鸟群或鱼群的行为，在优化任务中表现出色。它们还能够快速收敛到最佳解决方案并适应动态环境，从而增加对工程、金融和资料分析等领域各种应用的吸引力。

在应用方面，由于多机器人系统对分散控制和协调的需求不断增长，到 2032 年，机器人领域的群体智慧产业将大幅成长。群体智慧演算法使机器人能够表现出集体行为，从而提高其在搜索和救援、监视和探索等任务中的效率。群体机器人协作演算法研发的重大进步将进一步推动其采用，使其成为下一代机器人系统的关键技术。

从地区来看，由于研发投资不断增加，特别是在中国、日本和韩国等国家，亚太地区群体智慧市场将从 2024 年到 2032 年显着成长。蓬勃发展的科技产业以及人工智慧和机器人解决方案的日益普及正在推动对群体智慧技术的需求。政府推出的促进创新创业的措施也将刺激区域市场的扩张。

产业生态系统分析
供应商格局
- 技术提供者
- 系统整合商
- 终端用户
利润率分析
技术与创新格局
专利分析
重要新闻和倡议
监管环境
衝击力
- 成长动力
  - 提高群体智慧在解决巨量资料问题的适用性
  - 运输和物流领域越来越多地采用群体智能
  - 自治系统的发展
  - 工业4.0的崛起
  - 技术进步
- 产业陷阱与挑战
  - 开发和部署成本高
  - 认识和理解有限
成长潜力分析
波特的分析
PESTEL分析

第 4 章：竞争格局

介绍
公司市占率分析
竞争定位矩阵
战略展望矩阵

第 5 章：市场估计与预测：依型号，2021 - 2032

主要趋势
蚁群优化
粒子群最佳化
其他的

第 6 章：市场估计与预测：依能力划分，2021 - 2032 年

主要趋势
最佳化
聚类
调度
路由

第 7 章：市场估计与预测：依应用分类，2021 - 2032

主要趋势
机器人技术
无人机
人类蜂拥而至

第 8 章：市场估计与预测：按最终用户划分，2021 - 2032 年

主要趋势
运输与物流
- 最佳化
- 聚类
- 调度
- 路由
机器人与自动化
- 最佳化
- 聚类
- 调度
- 路由
卫生保健
- 最佳化
- 聚类
- 调度
- 路由
零售与电子商务
- 最佳化
- 聚类
- 调度
- 路由
其他的
- 最佳化
- 聚类
- 调度
- 路由

第 9 章：市场估计与预测：按地区，2021 - 2032

主要趋势
北美洲
- 我们
- 加拿大
欧洲
- 英国
- 德国
- 法国
- 义大利
- 西班牙
- 俄罗斯
- 北欧人
- 欧洲其他地区
亚太地区
- 中国
- 印度
- 日本
- 韩国
- 澳新银行
- 新加坡
- 亚太地区其他地区
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
- 拉丁美洲其他地区
MEA
- 阿联酋
- 南非
- 沙乌地阿拉伯
- MEA 的其余部分

第 10 章：公司简介

Agilox Services GmbH
Apium Swarm Robotics
Axon Enterprise, Inc
Berkeley Marine Robotics Inc.
Boston Dynamics
Continental AG
ConvergentAI, Inc
DoBots
Enswarm
Hydromea
Kim Technologies
PowerBlox
Robert Bosch GmbH
Sentien Robotics
SSI Schafer - Fritz Schafer
SwarmFarm Robotics
Swarm Technology
Swisslog Holding AG
Unanimous AI
Valutico

简介目录

Product Code: 8689

Swarm Intelligence Market size is projected to expand at over 38.5% CAGR from 2024 to 2032. The increasing complexity of problems in various industries, such as logistics, finance, and healthcare is driving the demand for numerous innovative solutions. Swarm intelligence algorithms offer efficient problem-solving capabilities by mimicking collective behavior observed in natural swarms. Additionally, advancements in artificial intelligence (AI) and machine learning (ML) technologies are enhancing the performance and scalability of swarm intelligence systems.

Rising adoption in autonomous vehicles, robotics, and optimization tasks is also increasing the market appeal. Growing collaborative research efforts and investments by governments and private organizations are further facilitating the development and commercialization of swarm intelligence solutions. For instance, in April 2024, Microsoft unveiled Phi-3-mini, the first of its small language models (SLMs)to broaden its customer base with cost-effective AI options while affirming its commitment to transformative technology to revolutionize work and society.

The overall industry is categorized into model, capability, application, end-user, and region.

Based on model, the swarm intelligence market from the particle swarm optimization (PSO) segment will expand at robust CAGR between 2024 and 2032, due to the simplicity, efficiency, and scalability of the algorithm. PSO algorithms excel in optimization tasks by simulating the behavior of bird flocks or fish schools. They also have ability to converge quickly to optimal solutions and adapt to dynamic environments, subsequently increasing their appeal for various applications in fields like engineering, finance, and data analytics.

With respect to application, the swarm intelligence industry from the robotics segment will grow at substantial rate up to 2032, owing to the growing need for decentralized control and coordination in multi-robot systems. Swarm intelligence algorithms enable robots to exhibit collective behavior, enhancing their efficiency in tasks like search and rescue, surveillance, and exploration. Significant advancements in swarm robotics R&D of collaborative algorithms will further drive their adoption, making it a key technology for the next generation of robotic systems.

Regionally, the Asia Pacific swarm intelligence market will depict notable growth from 2024 to 2032, on account of the increasing R&D investments, particularly in countries including China, Japan, and South Korea. The burgeoning tech industry and the growing adoption of AI and robotics solutions are driving the demand for swarm intelligence technologies. The launch of government initiatives to promote innovation and entrepreneurship will also spur the regional market expansion.

Chapter 1 Methodology & Scope

1.1 Research design
- 1.1.1 Research approach
- 1.1.2 Data collection methods
1.2 Base estimates and calculations
- 1.2.1 Base year calculation
- 1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
- 1.4.1 Primary sources
- 1.4.2 Data mining sources
1.5 Market definitions

Chapter 2 Executive Summary

2.1 Industry 360 degree synopsis, 2021 - 2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Supplier landscape
- 3.2.1 Technology providers
- 3.2.2 System integrator
- 3.2.3 End users
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Patent analysis
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Impact forces
- 3.8.1 Growth drivers
  - 3.8.1.1 Increasing applicability of swarm intelligence for solving big data problems
  - 3.8.1.2 Rising adoption of swarm intelligence in transportation and logistics
  - 3.8.1.3 Growth of autonomous systems
  - 3.8.1.4 Rise of Industry 4.0
  - 3.8.1.5 Advancement in technology
- 3.8.2 Industry pitfalls & challenges
  - 3.8.2.1 High development and deployment costs
  - 3.8.2.2 Limited awareness and understanding
3.9 Growth potential analysis
3.10 Porter's analysis
3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Model, 2021 - 2032 ($Mn)

5.1 Key trends
5.2 Ant colony optimization
5.3 Particle swarm optimization
5.4 Others

Chapter 6 Market Estimates & Forecast, By Capability, 2021 - 2032 ($Mn)

6.1 Key trends
6.2 Optimization
6.3 Clustering
6.4 Scheduling
6.5 Routing

Chapter 7 Market Estimates & Forecast, By Application, 2021 - 2032 ($Mn)

7.1 Key trends
7.2 Robotics
7.3 Drones
7.4 Human swarming

Chapter 8 Market Estimates & Forecast, By End Users, 2021 - 2032 ($Mn)

8.1 Key trends
8.2 Transportation & logistics
- 8.2.1 Optimization
- 8.2.2 Clustering
- 8.2.3 Scheduling
- 8.2.4 Routing
8.3 Robotics & automation
- 8.3.1 Optimization
- 8.3.2 Clustering
- 8.3.3 Scheduling
- 8.3.4 Routing
8.4 Healthcare
- 8.4.1 Optimization
- 8.4.2 Clustering
- 8.4.3 Scheduling
- 8.4.4 Routing
8.5 Retail & E-commerce
- 8.5.1 Optimization
- 8.5.2 Clustering
- 8.5.3 Scheduling
- 8.5.4 Routing
8.6 Others
- 8.6.1 Optimization
- 8.6.2 Clustering
- 8.6.3 Scheduling
- 8.6.4 Routing

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2032 ($Mn)

9.1 Key trends
9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Italy
- 9.3.5 Spain
- 9.3.6 Russia
- 9.3.7 Nordics
- 9.3.8 Rest of Europe
9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 South Korea
- 9.4.5 ANZ
- 9.4.6 Singapore
- 9.4.7 Rest of Asia Pacific
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
- 9.5.4 Rest of Latin America
9.6 MEA
- 9.6.1 UAE
- 9.6.2 South Africa
- 9.6.3 Saudi Arabia
- 9.6.4 Rest of MEA