As the number of connected IoT devices continues to rise exponentially, there’s an urgent need for robust frameworks that can effectively manage and analyse the data generated. The other key factor for enhancing the AIoT market is the need for automation and efficient running of activities. In the modern world, most companies are increasingly oriented towards implementing AIoT systems in their marketing strategies to enhance operational efficiency while reducing costs. The need to enhance user experience and provide personalization plays a crucial role in the growing AIoT market, enabling businesses to respond quickly and in a more personalized manner to their customers' needs when combined with IoT devices, which is appealing to many businesses in this era.

Platforms hold the largest market share

In the AloT market, platforms help develop and deploy AI solutions, thereby enhancing the performance and functionality of IoT systems. These platforms serve multiple purposes and are categorised into various subcategories.

• IoT device management is a platform that oversees the entire life cycle of IoT devices, from installation and operations to maintenance and upgrades. This process aims to ensure that the designed figures are used effectively and safely for the period for which they were intended.
• IoT application enablement platforms are the platforms that collect the requirements needed for the development and monetisation of AIoT applications. This enables the integration of various devices and information, making it easier for application developers to create and manage applications that process data generated from IoT devices.
• IoT connectivity management platforms and services are designed to manage data flow within the network and between IoT devices and the cloud. An IoT cloud is defined as a service that provides a flexible architecture for storing, managing, and analysing large quantities of IoT data to enable better and quicker business decisions. IoT advanced analytics utilises big data analytics and AI techniques to analyse performance data collected from IoT devices, providing actionable insights that can help improve operations.

Edge-based AIoT is projected for strong growth

Edge-based AloT implementations leverage the advantage of processing data closer to the IoT devices or at the extremities, thereby reducing the dependency on high bandwidths and the latencies associated with data analysis. AloT systems with edge characteristics are managed into three major layers: the collection terminal, connectivity, and edge layer, each performing its designated functions. Specific hardware components in the collection terminal layer include sensors, vehicles, embedded systems, tags, and active mobile components that are wired to gateways through existing electrical lines. In this case, the connectivity layer also possesses field gateways that connect with the collection terminal layer using these power transmission lines. Finally, the edge layer includes functionalities such as data warehouses, data processing resources, and even insight generators within the system.

Key players

The major vendors covered in the AIoT market and named within the report include IBM, Cisco, AWS, Google, Microsoft, Oracle, HPE, Intel, Hitachi and SAP.