Artificial Intelligence Takes on The Edge

Posted on

Edge devices are used in IoT to perform computing functions. Artificial intelligence (AI) employs machine learning to power digital assistants, smart phones and autonomous factories. Previously, much data processing for AI applications occurred over the cloud, requiring massive loads of bandwidth. But with new and continually improving microprocessors, AI processing can occur within edge devices: meet edge AI.

Edge AI Advantages

By processing data in edge devices, latency is reduced on the cloud. Monetary costs of bandwidth and cloud services are also reduced. Edge devices increase security since data is processed locally instead of sent over an internet connection. Edge AI improves real-time decision-making since data can be transferred closer to the applicable device.

Edge AI Applications

Smart phones and digital assistants already use edge AI. Consumers use it when they ask Siri or Alexa a question or give a verbal command. But it’s taken advancements in microprocessors to bring edge AI to larger applications.

Surveillance & Monitoring

Video cameras that constantly stream place a heavy load on the cloud. With edge AI, smart cameras can locally process data and transfer less over the internet. Edge AI also assists with the processing power of computer vision, facial recognition and audio detection for greater response time and efficiency.

Autonomous Vehicles & Drones

Autonomous cars rely on edge AI for real-time responses. With edge AI advancements, data is processed more quickly, allowing for improved response and safety. Drones will similarly benefit from improved edge AI in object recognition and tracking.

Industrial Automation

Factories may employ hundreds of machines, and making those machines smart involves massive amounts of data. The bandwidth cost of equipping those machines with AI may be more than some factories can handle. Edge AI allows for less costly and more efficient factory automation and robotics. It also improves the response time of machines.

Wearable Devices

Wearables devices collect massive amounts of data about human bodies. Common consumer wearables collect basic information like respiratory rate, heart rate, temperature and sleep cycles, which could provide early indications of disease. Edge AI enables complex computations of collected data for illnesses such as heart disease.

Medical Monitoring & Connected Healthcare

Edge AI will aid advancements in no-contact medical monitoring such as fever detection and hospital robotic aids. It will assist in the use of AI in hospital procedures and disease diagnoses, even enabling the detection of diseased tissue in the operating room.

Text & Speech Recognition

Though smart phones and digital assistants already use edge AI, advances in the technology improve their responsiveness and efficiency. With edge AI, these devices and chatbots will better interpret speech and input text.

Defense

The U.S. military has turned to AI for technology advancements. The Air Force foresees an AI fleet of wingman drones, and the military seeks AI to advance training and field operations. Edge AI improves the capabilities and efficiencies of these implementations.

Edge AI Market

Edge AI has the potential to improve the adoption of AI across industries as the technology becomes more efficient and less costly. The market for edge AI is expected to grow to $1.15 million by 2023 from $355 million in 2018.