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W-AI-STE and architecture waste management in buildings with the support of machine learning and artificial intelligence
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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

W-AI-STE and architecture waste management in buildings with the support of machine learning and artificial intelligence


Joint Event on 5th World Machine Learning and Deep Learning Congress and World Congress on Computer Science, Machine Learning and Big Data

August 30-31, 2018 Dubai, UAE

Kai Khalid Miethig

Tariq Faqeeh Engineering, Bahrain

Scientific Tracks Abstracts: J Comput Sci Syst Biol

Abstract :

W-AI-STE - The implementation of artificial intelligence and machine learning in the processes of waste management, segregation and collection in architectural developments. It is a new and unique form of combining the existing technologies with the latest technologies of artificial intelligence and machine learning for an ancient issue the humanity is facing ever since mankind exists: Waste management. Due to the fact that the population is increasing continuously and therewith the production of waste as well, why not using the available technologies and features for supporting that basic task, which no one wants to deal with and is a topic which is now becoming a worldwide problem. Anywhere in the world where humans are present and were present as well even in areas humans never have been waste can be found as a remains of human existence. As we all are aware of smart home systems, e.g. fingerprints for entrance control and access or speech control featuring various functions in the house, this AI and ML technologies can be as well implemented for our daily legacies: WASTE- W-AI-STE. All humans have a certain pattern of whatever they do or their habits, these pattern and habits are as well detectable in their waste. Most waste comes from food packing and packing in general, so people have their favorite food, ingredients and other recurrent favorites which can be recorded, tracked and analyzed with the help of artificial intelligence and machine learning. So in an early stage of developments for residential and commercial purpose the pattern can be used to develop the concept of waste management systems.

Biography :

Kai Khalid Miethig has completed his architectural study in 2004 at the University of Siegen, previous known as University of Applied Sciences of Siegen and gained further experience in waste management at Lobbe Environmental Consultancy. He has more than a decade experience in project management and lecturing. He is the Managing Director of Tariq Faqeeh Engineering in Bahrain, dedicated to enhance lifestyle and quality of living, offering various unique services for developers, government entities and individuals. He initiated the environmental awareness campaign “A Wave of Change” in cooperation with the Supreme Council of Environment Bahrain, German Embassy Bahrain and CleanUp Bahrain in 2017 and is providing/lectures on environmental awareness as well on the context and connection of architecture and waste management automation.

E-mail: miethig@web.de

kai@tfengineering.me

 

Google Scholar citation report
Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

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