Edge Computing Algorithms and Hardware Architectures for Deep Learning in Autonomous Systems

Methodology

Duration : six months - Price : ₹50000.00 - Place : Bengaluru (560075)Edge computing, often referred to as Mobile Edge Computing or Multi-Access Edge Computing, provides execution resources like memory, processing units, hardware accelerators, algorithms, system models or applications with networking close to the end users, typically within or at the boundary of operator networks.
Edge computing can also be placed at enterprise premises, for example inside factory buildings, in homes and vehicles, including trains, planes and private cars. These systems find applications in process automation, transportation management, healthcare automation, predictive control and maintenance in production units, self-driving cars, autonomous robots and rovers etc. The edge infrastructure can be managed or hosted by communication service providers or other types of service providers.
Several use cases require various applications to deployed at different sites. In such scenarios a distributed cloud is useful which can be seen as an execution environment for applications over multiple sites, including connectivity managed as one solution.

The main benefits edge solutions provide include low latency, high bandwidth, device processing and data offload as well as trusted computing and storage.