AI: Abbreviation for artificial intelligence
Artificial intelligence: Intelligence exhibited by machines. In computer science, an ideal "intelligent" machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".
Deep learning: A branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data by using a deep graph with multiple processing layers, composed of multiple linear and non-linear transformations.
Hardware device: A PCB in a case things
Internet of things: The internet working 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 that enable these objects to collect and exchange data.
IoT: Abbreviation for Internet of Things
IoT device: A small hardware device that includes electronics, software and connectivity
Machine learning: The subfield of computer science that "gives computers the ability to learn without being explicitly programmed".
Motion intelligence: (Imagimob definition): A technology used to understand how things, people and animals move, by applying artificial intelligence (AI) on raw sensor data.
Motion intelligence on the edge: (Imagimob definition): A technology used to understand how things, people and animals move by applying artificial intelligence (AI) on raw sensor data in the IoT device (not in the cloud).
Motion sensor: A sensor (electronics component) that generates raw sensor data. Accelerometer, gyroscope, magnetometer are motion sensors
PCB: A printed circuit board mechanically supports and electrically connects electronic components using conductive tracks, pads and other features etched from copper sheets laminated onto a non-conductive substrate. Components – capacitors, resistors or sensors – are generally soldered on the PCB.
Self-learning: Subfield of machine learning that includes unsupervised learning. No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end.