Join Dr Rami Zewail, from Smart Empower Innovation Labs, for a talk and panel discussion on opportunities and challenges for IIoT. The event will be held as part of the Vertical Track session on Energy and Power at the 6th IEEE World Forum on the Internet of Things.
With the emergence of the Industrial Internet of Things (IIoT) and low power efficient processors,
Embedded Machine learning and edge computing have recently received much interest over a wide range of fields including predictive maintenance, tele-medicine, and wearables. Big players like Google and Microsoft are now moving from Cloud-based intelligence to Embedded Edge-based
intelligence. Edge computing refers to processing, analyzing and storing data at the origin hardware
layer instead of the Cloud. Lately, Edge computing has drawn a lot of attention as a key infrastructure and the backbone in IIoT and Industry 4.0 initiatives. Edge Computing is about de-centralization of computing power and intelligence. This has potential to overcome a lot of the current challenges in BIG DATA and Cloud Computing. Examples of foreseen benefits include reduction of decision latency, enabling real-time intelligence, improved operational efficiency, and robustness of connected applications. On the other side, it is well known that the oil and gas industry has traditionally been slow in adopting new technologies and innovation. However, due to the current challenges in the industry, a lot of the companies are now turning towards digital transformation technologies as a means to optimize operations, and maximize financial gains.
In this talk, we discuss some of the challenges in the digital transformation of the Oil and Gas Industry. We discuss how recent advances in edge computing and de-centralized intelligence have the potential to accelerate the digital transformation of the Energy Industry
A new Hands-on Tutorial by Smart Empower Innovation Labs at the IEEE 6th World Forum on the Internet of Things, Louisiana, USA
AI-STREAM Digital Transformation Challenge Event : The BIG Data vs Sparse Data Challenge
Efficient Handling of BIG Data is an essential building block of digital transformation and Industry 4.0 Initiatives.In this hands-on tutorial, we would present an overview of the role of sparsity in Machine Learning with application to Industrial Internet-of-Things (IIoT). The event would also include hands-on demonstration on how sparse data analytics can help overcome some of the challenges in BIG DATA.
The event is concluded with the release of a digital transformation competition with the theme “BIG Data vs Sparse Data”. The competition would be hosted on our AI-STREAM platform.
For more information, please check the event’s official link here and AI-STREAM
LiTEChain is a secure Intelligent asset tracking solution that merges between BlockChain, IoT, and machine learning technology.
Leveraging on cutting edge expertise in encryption security, machine learning, and IoT, LiTEChain provides a secure Intelligent Asset tracking solution that merges between blockchain, IOT, and Machine Learning technologies.
This course is a 360 overview of embedded systems paradigm: competencies needed, how to get prepared, and what to expect. The course is also a good tool to assess your skills and understand what background and experience is needed to become an embedded systems developer.