Machine Learning Sensors

The last decade has seen a surge in commercial applications using machine learning (ML). Similarly, marked improvements in latency and bandwidth of wireless communication have led to the rapid adoption of cloud-connected devices, which gained the moniker Internet of Things (IoT). With such technology, it became possible to add intelligence to sensor systems and devices, enabling new technologies such as Amazon Echo, Google Nest, and other so-called "smart devices." However, these devices offer only the illusion of intelligence and are merely vessels for submitting and receiving queries from a centralized cloud infrastructure. This cloud processing leads to concerns about where user data is being stored, what other services it might be used for, and who has access to it.7 More recently, efforts have progressed in dovetailing the domains of IoT and machine learning to embed intelligence directly on the device, known as tiny machine learning (TinyML).10