As the Co-Founder & CEO at Tekskills Inc. partners with clients globally in their digital transformation journeys, the conversation around the Internet of Things (IoT) has shifted towards the Artificial Intelligence of Things (AIoT) in recent years.
IoT involves connecting various devices, peripherals, and appliances to a network to gather insights. On the other hand, AIoT integrates AI into the IoT ecosystem, enhancing connectivity with intelligence.
AIoT devices incorporate AI into IoT networks, enabling seamless data exchange between applications. This fusion of connectivity and intelligence is likened to the nervous system and brain analogy.
AIoT applications span across different sectors. In networked mobility, AIoT aids in optimizing routes and parking. In networked homes, it optimizes device usage, while in networked manufacturing, it enhances equipment maintenance and process optimization.
AIoT's impact extends to offices, stores, healthcare, and oil and gas industries. It enables access control, consumer behavior analysis, patient monitoring, and predictive maintenance, among other benefits.
Looking ahead, the global device count is projected to surpass 25 billion by 2030, driving AIoT adoption. Companies venturing into AIoT projects should focus on infrastructure, start with small-scale models, and prioritize security measures.
AIoT leverages technologies like deep learning, machine learning, and natural language processing. However, challenges such as connectivity issues, complexity, security risks, and high costs need to be addressed for successful AIoT implementation.
While AIoT offers numerous advantages, ensuring human oversight and addressing potential failures are critical. Understanding the technology landscape and mitigating risks will be key for organizations embracing AIoT in their digital transformation strategies.
