Edge AI

Edge AI: A survey

“…Smart Home: Edge AI can be used to power smart home devices such as voice assistants, thermostats, and security cameras [161]. These devices use machine learning algorithms to learn user preferences and behaviour and make real-time decisions based on sensor data; Driverless Cars: Edge AI is being used in autonomous vehicles to process sensor data and make decisions in real-time, allowing the vehicle to react quickly to changes in its environment [162], Healthcare: Edge AI can be used to analyse medical data from wearable devices and sensors to monitor patients in real-time, detect abnormalities, and provide early warnings for potential health issues [162], Business Marketing: Edge AI can be used to analyse customer data, including purchase history and behaviour, to provide personalized recommendations and improve customer experiences [163]. Edge AI has the potential to revolutionize industries by enabling intelligent and autonomous devices that can make real-time decisions based on sensor data [164].…”

“…Internetworking: It is typically difficult to transport significant volumes of data and models to and from smart edge devices because these systems frequently have restricted or inconsistent network access [161]. Because of this, the quality and dependability of AI algorithms that rely on real-time data inputs might also be negatively impacted [162]. Data confidentiality and security: Edge computing devices frequently gather and handle confidential material, such as records related to an individual's health or banking transactions [145].…”

“…Real-time data analysis: Edge computing offers real-time data analysis by executing computations at the network's periphery, hence fueling apps like driverless cars, smart buildings, and advanced robotics [162]. Minimize delay: Compared to transmitting data to a centralised data centre, the computation for data handled via edge computing is much shorter.…”

“…Without AI, it would be impossible for programmes to handle the vast variety of text, speech, and video data that they are asked to process [161]. Cost: By moving to compute resources towards the edge, applications may make do with less bandwidth via the Internet, resulting in significant savings in communication expenses [162]. Privacy: Because AI could examine actual information without revealing it to humans, it is a safer bet for people to entrust their look, tone, medical image, and other sensitive data to be studied in a clinical setting [162].…”

“…Cost: By moving to compute resources towards the edge, applications may make do with less bandwidth via the Internet, resulting in significant savings in communication expenses [162]. Privacy: Because AI could examine actual information without revealing it to humans, it is a safer bet for people to entrust their look, tone, medical image, and other sensitive data to be studied in a clinical setting [162]. By keeping such data on-premises, Edge AI additionally protects users' confidentiality, sending just the results of their analyses and observations to the cloud [185].…”