Digital twin: Empowering edge devices to be intelligent

Abstract

Abstract Edge/fog devices, such as machineries at manufacturing floors, instruments in hospitals, digital assistants with human beings, equipment and appliances at factories, wares and utensils at homes, cameras at important places such as airports, railway stations, retail stores and malls, entertainment plazas, eating joints, stadiums, and auditoriums are all set to join in the mainstream computing as they are being stuffed with increased processing capabilities, memory and storage capacities. They are also being connected with one another in the vicinity directly and indirectly through a middleware solution. Also remotely held, cloud-hosted and cyber applications and databases are also being integrated with ground-level edge/fog devices. Through such extreme connectivity and deeper integration, edge and fog devices are intrinsically and externally enabled to do real-time data capture, processing, analytics, knowledge discovery, decision-making and actuation. Precisely speaking, edge/fog devices and their clusters are all set to become the next-generation, highly optimized and organized IT infrastructure for producing and delivering real-time applications and services. In other words, edge/fog clouds are being dynamically established and sustained in order to provide a variety of service-oriented, event-driven, people-centric, mission-critical, knowledge-filled, and context-aware services for both professionals and commoners. Real-time sensor and streaming data analytics can be easily accomplished through edge clouds in order to supply personalized, predictive and prescriptive insights. Edge clouds are also getting synchronized with conventional clouds such as public, private, and hybrid clouds in order to facilitate comprehensive and historical data analytics. This chapter is for accentuating and articulating how edge devices become intelligent in their actions and reactions in conjunction with their respective digital twins.