Swarm intelligence is a branch of artificial intelligence based on the collective behaviour of self-organised, decentralised systems made up of relatively simple agents interacting with one another and their surroundings locally in many ways real swarms do. Over the past 20 years, there has been a surge in interest in swarm intelligence and bio-inspired computing in nearly every engineering, research, and business field.
To logically govern their operations, Swarm intelligence is heavily involved in the Internet of Things and IoT-based solutions. As IoT-based systems are complicated and comprise smart items, it takes decentralised solid algorithms supported by Swarm intelligence to tackle challenges of this magnitude. Due to their dynamic characteristics, such as wireless connection, device mobility, and information provision, the intelligent algorithms of S.I. can resolve the complex problems of IoT systems. S.I. algorithms are well-established and used in well-known aptitude-based challenges where real-time actions are effectively managed.
As per the report published by The Brainy Insights, the swarm intelligence market is anticipated to reach $447.53 Billion by 2032, at a CAGR of 35.33% from 2023 to 2032. Swarm intelligence is an emerging technology used in different industries such as logistics, transportation, healthcare, retail, e-commerce, etc. Many government and private organisations are exploring technology for deployment in space and military applications.
IoT, which enables information exchange and intelligent decision-making utilising commonplace gadgets, results from ongoing technological breakthroughs such as machine-to-machine communications and extensive data analysis. Swarm intelligence algorithms, on the other hand, aim to create positive interaction between agents independent of their cognitive level. Several people operate concurrently and sometimes cooperatively in S.I. algorithms to solve challenging nonlinear problems. Swarm intelligence can effectively utilise resources by making distributed data processing easier to implement among devices with limited resources.
The increased demand for optimisation caused by the Internet of Things can be fulfilled using S.I. methodologies. Because IoT-based systems utilise various technologies, including several protocols and data models, many users of numerous Internet-connected devices must bear expensive integration and maintenance costs when putting major IoT projects into practice. Swarm intelligence may be a strong contender to close this gap. Swarm intelligence can help a group of various IoT devices cooperate and share information, resulting in enhanced usefulness.
For instance, in the military, Swarm Intelligence has made deploying unmanned aerial vehicles and drones simpler since it allows the many gadgets to communicate with one another, allowing for timely and non-delayed completion of objectives. As a result, it can assist in resolving problems relating to the compatibility of defence equipment provided by various manufacturers using various generations of technology. These must be adaptable to different conditions and simple to utilise for the military. Swarm intelligence can be employed in mountain counterterrorism operations to help counterterrorism personnel with information and communication, ensuring effective command and tight collaboration.
Regional analysis
The North American region emerged as the largest neurostimulation device market, with a market share of 41.11% in 2022. North America had the largest revenue share in the past and is projected to maintain dominance in future years. Over the years, the US has made over $3 million in contributions to the global swarm intelligence sector. Additionally, the US has the most significant military budget and is launching swarm robots to alter how wars are conducted. The US is researching and developing cooperative, networked drones that can compete to defeat enemies.
The favourable initiatives by regional governments have increased the usage efficiency and Swarm intelligence in North America. Thus, most of the players are keen to expand their presence in such regions due to the growth of the space, automotive and robotics industries. Manufacturers are analysing the network requirements of such organisations and are thus penetrating deeper into such regions.
The optimisation segment is dominating the market with a market share of 41% in 2022
The capability segment is divided into optimisation, clustering, scheduling and routing. As of 2022, implantable devices accounted for the largest market share, around 41%. Over the past ten years, swarm intelligence-inspired optimisation techniques have become popular. They are distinguished by a decentralised mode of operation that resembles the behaviour of schools of fish, social insect swarms and flocks of birds. These methods’ resilience and adaptability make them superior to conventional techniques.
The robotics segment is dominating the market with a market share of 46% in 2022
The application segment is divided into robotics, drones and human swarming. As of 2022, implantable devices accounted for the largest market share, around 46%. By forming advantageous structures and behaviours resembling those seen in natural systems like birds, or fish, numerous robots work together to solve issues in swarm robotics. Swarm robotics studies how to create robot groups that work independently of any centralised control or external infrastructure.
The robotics & automation segment dominates the market, with a market share of 49% in 2022
The end-user segment is divided into transportation & logistics, robotics & automation, healthcare, retail & e-commerce and others. The robotics & automation segment is expected to have the highest market share of around 49% in 2022. Nano-robotics and macrobiotics are only two potential uses for swarm robotics. They could be applied to distributed sensing activities in the human body or micro-machinery. The application of swarm robotics in search and rescue operations is also possible. Swarm intelligence-optimised techniques are used by many automated models, which are employed in a variety of applications.
Competitive Analysis:
| Attribute | Description |
| The market size value in 2022 | $21.72 Billion |
| The market size value in 2032 | $447.53 billion |
| CAGR (2023 to 2032) | 35.33% |
| Segments Covered | Capability, Application and End-user |
| Companies Mentioned | Power-Blox AG, Sentien Robotics, LLC, Apium Swarm Robotics, Swarm Technology, Convergent A.I., Inc., Mobileye (Intel), Continental AG, Valutico, Robert Bosch GmbH, Unanimous A.I. |
| Regions Covered | North America, Europe, Asia Pacific, Latin America, Middle East & Africa |
About the report
The market is analysed based on value (USD Billion). All the segments have been analysed worldwide, regional, and country basis. The study includes the analysis of more than 30 countries for each part. The report analyses driving factors, opportunities, restraints, and challenges to gain critical market insight. The study includes Porter’s five forces model, attractiveness analysis, product analysis, supply, and demand analysis, competitor position grid analysis, distribution, and marketing channels analysis.
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