A self-driving car, also known as an autonomous car (AC), driverless car, or robotic car (robo-car), is a car that is capable of driving without human input. Self-driving cars are responsible for all driving activities including perceiving the environment, monitoring important systems, and controlling the vehicle, including navigating from origin to destination.
Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. While this initially appears to be a chicken or the egg problem, there are several algorithms known to solve it in, at least approximately, tractable time for certain environments. Popular approximate solution methods include the particle filter, extended Kalman filter, covariance intersection, and GraphSLAM. SLAM algorithms are based on concepts in computational geometry and computer vision, and are used in robot navigation, robotic mapping and odometry for virtual reality or augmented reality.
Telematics is an interdisciplinary field encompassing telecommunications, vehicular technologies, electrical engineering, and computer science. Telematics can involve any of the following:
Swarm robotics is an approach to the coordination of multiple robots as a system which consist of large numbers of mostly simple physical robots. ″In a robot swarm, the collective behavior of the robots results from local interactions between the robots and between the robots and the environment in which they act.″ It is supposed that a desired collective behavior emerges from the interactions between the robots and interactions of robots with the environment. This approach emerged on the field of artificial swarm intelligence, as well as the biological studies of insects, ants and other fields in nature, where swarm behaviour occurs.
Clock synchronization is a topic in computer science and engineering that aims to coordinate otherwise independent clocks. Even when initially set accurately, real clocks will differ after some amount of time due to clock drift, caused by clocks counting time at slightly different rates. There are several problems that occur as a result of clock rate differences and several solutions, some being more acceptable than others in certain contexts.
Edge computing in the context of cloud computing, is roughly about installing multiple servers in multiple places, so that a user of a cloud application is likely to be physically closer to a server than if all servers were in one place. This is meant to make applications faster. More broadly, it refers to any design that pushes computation physically closer to a user, so as to reduce the latency compared to when an application runs on a single data centre. In the extreme case, this may simply refer to client-side computing.
An indoor positioning system (IPS) is a network of devices used to locate people or objects where GPS and other satellite technologies lack precision or fail entirely, such as inside multistory buildings, airports, alleys, parking garages, and underground locations.
Wi-Fi positioning system is a geolocation system that uses the characteristics of nearby Wi‑Fi access point to discover where a device is located.
Urban computing is an interdisciplinary field which pertains to the study and application of computing technology in urban areas. This involves the application of wireless networks, sensors, computational power, and data to improve the quality of densely populated areas. Urban computing is the technological framework for smart cities.
Map matching is the problem of how to match recorded geographic coordinates to a logical model of the real world, typically using some form of Geographic Information System. The most common approach is to take recorded, serial location points and relate them to edges in an existing street graph (network), usually in a sorted list representing the travel of a user or vehicle. Matching observations to a logical model in this way has applications in satellites navigation, GPS tracking of freight, and transportation engineering.
Approximate computing is an emerging paradigm for energy-efficient and/or high-performance design. It includes a plethora of computation techniques that return a possibly inaccurate result rather than a guaranteed accurate result, and that can be used for applications where an approximate result is sufficient for its purpose. One example of such situation is for a search engine where no exact answer may exist for a certain search query and hence, many answers may be acceptable. Similarly, occasional dropping of some frames in a video application can go undetected due to perceptual limitations of humans. Approximate computing is based on the observation that in many scenarios, although performing exact computation requires large amount of resources, allowing bounded approximation can provide disproportionate gains in performance and energy, while still achieving acceptable result accuracy. For example, in k-means clustering algorithm, allowing only 5% loss in classification accuracy can provide 50 times energy saving compared to the fully accurate classification.
Implicit authentication (IA) is a technique that allows the smart device to recognize its owner by being acquainted with his/her behaviors. It is a technique that uses machine learning algorithms to learn user behavior through various sensors on the smart devices and achieve user identification. Most of the current authentication techniques, e.g., password, pattern lock, finger print and iris recognition, are explicit authentication which require user input. Comparing with explicit authentication, IA is transparent to users during the usage, and it significantly increases the usability by reducing time users spending on login, in which users find it more annoying than lack of cellular coverage.
An AI accelerator, deep learning processor, or neural processing unit is a class of specialized hardware accelerator or computer system designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and machine vision. Typical applications include algorithms for robotics, Internet of Things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability. As of 2024, a typical AI integrated circuit chip contains tens of billions of MOSFET transistors.
Cache prefetching is a technique used by computer processors to boost execution performance by fetching instructions or data from their original storage in slower memory to a faster local memory before it is actually needed. Most modern computer processors have fast and local cache memory in which prefetched data is held until it is required. The source for the prefetch operation is usually main memory. Because of their design, accessing cache memories is typically much faster than accessing main memory, so prefetching data and then accessing it from caches is usually many orders of magnitude faster than accessing it directly from main memory. Prefetching can be done with non-blocking cache control instructions.
Transition refers to a computer science paradigm in the context of communication systems which describes the change of communication mechanisms, i.e., functions of a communication system, in particular, service and protocol components. In a transition, communication mechanisms within a system are replaced by functionally comparable mechanisms with the aim to ensure the highest possible quality, e.g., as captured by the quality of service.
RF CMOS is a metal–oxide–semiconductor (MOS) integrated circuit (IC) technology that integrates radio-frequency (RF), analog and digital electronics on a mixed-signal CMOS RF circuit chip. It is widely used in modern wireless telecommunications, such as cellular networks, Bluetooth, Wi-Fi, GPS receivers, broadcasting, vehicular communication systems, and the radio transceivers in all modern mobile phones and wireless networking devices. RF CMOS technology was pioneered by Pakistani engineer Asad Ali Abidi at UCLA during the late 1980s to early 1990s, and helped bring about the wireless revolution with the introduction of digital signal processing in wireless communications. The development and design of RF CMOS devices was enabled by van der Ziel's FET RF noise model, which was published in the early 1960s and remained largely forgotten until the 1990s.
Moustafa Youssef is an Egyptian computer scientist who was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2019 for contributions to wireless location tracking technologies and a Fellow of the Association for Computing Machinery (ACM) in 2019 for contributions to location tracking algorithms. He is the first and only ACM Fellow in the Middle East and Africa.
Static application security testing (SAST) is used to secure software by reviewing the source code of the software to identify sources of vulnerabilities. Although the process of statically analyzing the source code has existed as long as computers have existed, the technique spread to security in the late 90s and the first public discussion of SQL injection in 1998 when Web applications integrated new technologies like JavaScript and Flash.
Internet of vehicles (IoV) is a network of vehicles equipped with sensors, software, and the technologies that mediate between these with the aim of connecting & exchanging data over the Internet according to agreed standards. IoV evolved from Vehicular Ad Hoc Networks, and is expected to ultimately evolve into an "Internet of autonomous vehicles". It is expected that IoV will be one of the enablers for an autonomous, connected, electric, and shared (ACES) Future Mobility.
Spatial embedding is one of feature learning techniques used in spatial analysis where points, lines, polygons or other spatial data types. representing geographic locations are mapped to vectors of real numbers. Conceptually it involves a mathematical embedding from a space with many dimensions per geographic object to a continuous vector space with a much lower dimension.
