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DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in IoT (AIoT) Convergence: Technologies, Platforms, Applications and AIoT Services in Industry Verticals 2019 - 2024" report has been added to ResearchAndMarkets.com's offering.

This research provides a multi-dimensional view into the AI market including analysis of embedded devices and components, embedded software, and AI platforms. This research also assesses the combined Artificial Intelligence (AI) marketplace including embedded IoT and non-IoT devices, embedded components (including AI chipsets), embedded software and AI platforms, and related services.

This research evaluates leading solution providers including hardware, software, integrated platforms, and services. It includes quantitative analysis with forecasts covering AI technology and systems by type, use case, application, and industry vertical. The forecast also covers each major market sector including consumer, enterprise, industrial, and government. It also includes specific industry recommendations with respect to Artificial Intelligence hardware, software, and services.

This research also represents the most comprehensive research covering core IoT hardware, software, and firmware as well as supporting technologies such as AI and edge computing. It evaluates leading vendors, products, and services offerings. The quantitative portion of this research provides detailed forecasts for the global and regional IoT technology market for 2019 to 2024. It also includes specific industry recommendations in key areas such as data analytics and AI hardware, software and services.

AI represents a combination of various technologies including Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Speech Recognition, Context-Aware Processing, Neural Network, and Predictive APIs. AI will be found in virtually everything, ranging from individual products and applications to widespread systems and networks. Network infrastructure and computing equipment will rely upon AI algorithms for decision making while at the device level AI will be built into electronics at the chipset level.

IoT networks and systems consist of a vast array of hardware, software and firmware elements including semiconductors and embedded devices, sensors, controllers, and gateways. Communication between end-nodes and IoT platforms depends upon wired and wireless networking based on LTE and emerging 5G networks as well as many non-cellular low power WAN methods. IoT infrastructure and platforms consist of hardware, software, and Application Programming Interfaces (API) with APIs acting as a key element providing access to IoT platforms for intra-network signaling/messaging as well as communications on an intersystem basis. IoT APIs also provide a means for provisioning and administration of IoT devices, data, and applications.

IoT hardware may be both physical and virtualized. IoT software may be both deterministic in terms of programming and outcomes as well as programmatic thanks to IoT APIs and communications platforms as a service (CPaaS). IoT APIs may be open, proprietary, and/or pre-built connectors for specific purposes. Taken together, IoT hardware, software and APIs provide the basis for IoT platforms, which consist of many different programs, algorithms, and operating systems.

Current IoT networks are largely deterministic in nature, relying upon autonomic systems making decisions based on predetermined rules that take action based upon the occurrence of specific events. The Artificial Intelligence of Things (AIoT) will become increasingly important as the AIoT market evolves to allow IoT networks and systems to become more cognitive. The emerging AIoT market will enable systems to become increasingly more cognitive, making decisions based on context and experience.

It is important to recognize that intelligence within the IoT technology market is not inherent but rather must be carefully planned. AIoT market elements will be found embedded within software programs, chipsets, and platforms as well as human-facing devices such as appliances, which may rely upon a combination of local and cloud-based intelligence.

Just like the human nervous system, IoT networks will have both autonomic and cognitive functional components that provide intelligent control as well as nerve end-points that act like nerve endings for neural transport (detection and triggering of communications) and nerve channels that connect the overall system. The big difference is that the IoT technology market will benefit from engineering design in terms of AI and cognitive computing placement in both centralized and edge computing locations.

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Global Artificial Intelligence in IoT (AIoT) Convergence Market Report 2019-2024: Technologies, Platforms, Applications and AIoT Services in Industry...