Fieldlab Smart Energy

The manufacturing and maintenance industry in IJmond emits too much CO2, wastes too much energy and - in order to remain competitive in the future and to have a license to operate - must invest in reducing emissions and energy consumption. To be able to act, both large companies and SMEs must gain insight into their own current energy consumption in production and maintenance processes (and that of customers), get a grip on energy consumption and emissions and then analyze where the profits lie. With the use of sensors, resulting data, analytics and (tiny) machine learning, these companies in IJmond can take this step. Tiny Machine Learning in particular appears to be an interesting and applicable technology for this.

Building knowledge and gaining experience
Applying these smart technologies and anticipating them cannot be done by companies alone. Asset owners, suppliers, maintenance companies, system integrators, sensor companies and educational and knowledge institutions need each other to build knowledge and gain experience: to take steps in energy efficiency through process optimization, predictive maintenance and emission reduction based on sensor deployment, machine learning and data analysis: from data to information, knowledge and wisdom.

Objectives
The objective of Fieldlab Smart Energy is to make smart (new) digital technologies (smart sensoring and tiny machine learning) that can contribute to cleaner and smarter business processes more accessible to the SME business community. Techport does this by working with both large companies and SMEs and educational institutions to test, demonstrate results and train employees of these companies on knowledge and application of these technologies. By undertaking these activities from the Fieldlab collaboration, the functional use of data becomes accessible and deployable and companies can produce cheaper, faster, safer, cleaner and more flexible. In a learning community Smart Energy, companies and educational institutions share technologies and results of use cases and work on the business cases (upscaling) of the technology. In this way we contribute to solving problems in the field of energy, health of systems and processes , safety and nuisance and we contribute to the development of future-proof skills of employees and we democratize Machine Learning and Artificial Intelligence.

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Fieldlab Smart Energy is made possible in part by a grant from the Just Transition Fund IJmond