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Understanding Impact of AI on IoT

Artificial Intelligence

Artificial Intelligence (AI)

AI is based on Deep Learning algorithms. Deep Learning involves automatic feature detection from data. AI techniques can be applied to a range of Data types including: Images and sound (CNNs), Transactional data, Sequences (LSTMs), Text (Natural Language Processing) and Behaviour (Reinforcement Learning).

Internet of things (IoT)

The Internet of things (IoT) is the inter-networking of physical devices, vehicles (also referred to as “connected devices” and “smart devices”), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data.

IoT will produce a treasure trove of big data – data that can help cities predict accidents and crimes, give doctors real-time insight into information from pacemakers or bio-chips, enable optimized productivity across industries through predictive maintenance on equipment and machinery, create truly smart homes with connected appliances and provide critical communication between self-driving cars. There are endless possibilities that IoT brings to the world for betterment.

Impact of AI on IoT

AI techniques extend machine learning strategies in four ways:

  1. Complex decisions based on detecting a large number of hidden or hierarchical influencers
  2. Self learning
  3. Self-healing
  4. Autonomous decision making

AI techniques extend traditional Machine learning strategies(like Anomaly detection). We have to now address questions such as:

  • What decisions are suited for AI and there Impacts?
  • Where can they be made?
  • How can the decisions be made and propagated? (mechanism)

This involves implementation of models like the Digital Twin and Continuous learning. The domains most likely to be impacted by the deployment of AI with IoT include: Automotive – Self driving cars; Smart cities and Cloud robotics, Decision making Systems.


Looking into the learning and decisions involved and implementation complexities there arises a need of new breed of engineers with expertise in learnings from Electronics(IoT) with  Machine learning, AI, Robotics, Cloud  and Data management (devops). AI will be Key for the success of IoT.

IoT and AI work in juxtapose and with deep integration achieve the best of the results in the field of decision making systems and universal growth of the human kind

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