Cloud computing is a widely used technology that provides theoretically unlimited computing
and storage capabilities, and efficient communication services for transferring terabyte flows
between data centers in an easy way. All these features make cloud computing a promising
choice for supporting IoT services and applications. This course covers the various aspects of the
integration of IoT, Networking and Cloud computing. There are significant benefits in the
integration of IoT devices with cloud computing systems and network infrastructures along with
different services. Networking solutions specifically designed for the exploitation of Cloud
services in IoT scenarios assume a crucial role. Also, virtualization techniques make pools of
(virtual) sensors and actuators available as new types of on-demand resources over the Cloud
that can be integrated with other resources and exposed as cloud-based services. They allow
developers to differentiate circuits aimed at IoT interactions, to increase Cloud scalability and
efficiency in service provisioning.
The operating system (OS) is the system software that manages computer hardware and software resources and provides common services for programs. Considering the resource constraints of typical sensor nodes in wireless sensor networks, a new approach is required for OS design in WSN. The operating systems for WSNs should be flexible component-based and application-specific specially designed for these types of networks. It should also support concurrent programs with very low memory requirements. This module focuses on this special type of operating system.
Creativity, together with the making of ideas into fruition, is essential for progress. Today the evolution from an idea to its application can be facilitated by the implementation of Fabrication Laboratories, or FabLabs, having affordable digital tools for prototyping. FabLabs aiming at scientific research and invention are now starting to be established inside Universities and Research Centers to support STEM education and for community development. In this module we teach the basics of handling the fabrication of PCBs prototype casing using 3D printers.
The operating system (OS) is the system software that manages computer hardware and software resources, and provides common services for programs. Considering the resource constraints of typical sensor nodes in wireless sensor network, a new approach is required for OS design in WSN. The operating systems for WSNs should be flexible component based and application specific specially designed for these types of networks. It should also support concurrent programs with very low memory requirements. This module focuses on this special type of operating system.
This module is concerned with the design and implementation of embedded and distributed analytics for IoT applications such as: predictive maintenance, person-centered health analytics, anomaly detection, adaptive automatic scheduling, self-driving cars, smart cameras, and so on. A particular focus will be set on Artificial Intelligence (AI) and Machine Learning(ML) algorithms. Embedded/Edge and Distributed analytics has gained a lot of attention in the last years as a solution to solve problems created by Cloud-based analytics such as the big data deluge, data Privacy & Security, limited bandwidth for data streaming transmission and large latency for feedback to edge devices. After completing this module, the student will have gained the necessary skills to undertake research in embedded AI and ML. Furthermore he/she will be able to design and prototype a basic embedded and distributed analytics application
Welcome to the Module "ECS6261: ULTRA-LOW POWER DESIGN TECHNIQUES FOR IoT DEVICES"
This module aims at inculcating techniques of minimizing the amount of energy required to actually operate IoT devices, networks and systems by in part; minimizing the number of required IoT sensors that needed to cover specific area, in using a true battery-free device, by designing and implementing energy harvesting circuits that can help IoT sensors utilize energy harvested directly from the environment; e.g. Radio Frequency (RF), light, motion, and vibration, or integrated/hybrid architectures of these. Standards and optimization techniques for ultra-low power and energy harvesting design architectures shall be discussed and prototyped.