Disruptive AI approach for Smart-City Networks: Novel characterization and protection from Urban Air Pollution penetration into commercial and residential buildings.

Wednesday 18th October 16:00 - 16:45

Management Theatre

This study presents a revolutionary and disruptive scientific mathematical characterization of the kinetics of gaseous ambient air pollution. It also introduces a novel scientific approach to protecting occupants of numerous commercial and residential buildings from harmful exposure to the most prevalent air pollutants, which have been shown to have a substantial detrimental impact on public health. These findings are supported by scientific literature and align with the conclusions drawn by the World Health Organization through their extensive meta-analysis projects.

Urecsys has acquired unprecedented databases and developed unique analysis tools to reveal and determine the ingress of urban air pollution into buildings. The behaviour of these small gaseous molecules in real-time is in fact, the most dominant factor that determines the actual indoor air quality of commercial and residential buildings (considering buildings that comply with ventilation standards).

These novel Urban AI Networks are fully functional, proven beyond any doubt, and are continuously controlling & optimizing numerous sorts of buildings in real-time.

During the session, we will show several case studies from several different types of buildings. Amongst the buildings being optimized by Urecsys' Smart City AI Networks are the HQs and offices of Google, Microsoft, Schneider Electric, Intel, HP, General Motors, Teva Pharmaceuticals, Fiverr, WeWork, Nestle, Unilever, the Israeli Ministry of Health, the residence of the World Health Building Council, and many more.

Delegates will learn of a novel scientific breakthrough in the fields of public health in the urban environment, the application of Machine Learning & AI in building optimization, and in the field of Urban / Industrial / Transportational Air Pollution.

Furthermore, we will provide a concise overview of the health impacts of urban air pollution, highlighting the exact effect of air pollution levels on the prevalence of diseases such as lung cancer, stroke, and more.

The delegates will also be introduced to a unique Smart-City Software System which has been proven beyond a doubt to reduce the exposure of building inhabitants to the most harmful air pollutants which are the leading environmental cause of death and disease, and which can be implemented into any building.

Additionally, we will investigate the energy reduction aspect, resulting from the system's implementation, providing a comprehensive explanation which incorporates case studies from many different climates.

This groundbreaking study offers a distinctive assessment of indoor air pollution levels experienced within office spaces, featuring multiple case studies. It provides a comprehensive summary of the apparent health implications resulting from exposure to these pollution levels, drawing support from esteemed top-tier medical and scientific journals and presented by a prominent cancer research and medical sciences authority.

The study introduces an innovative, practical, and cost-effective solution that significantly reduces the exposure to air pollution level. This solution is easy to implement, making it an essential piece of knowledge for managers, engineers, and advisors in the building industry. Understanding and adopting these findings can contribute significantly to promoting healthier indoor environments and safeguarding the well-being of occupants while optimizing building operations utilizing the most cutting edge abilities.

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Maor Ganz

Senior researcher in Urecsys, Head of Machine Learning department, Chief Technology Officer

Urecsys - Urban Ecology Systems

Dr. Maor Ganz is a leading researcher from the Hebrew University. He is among the most prominent Israeli researchers in the field of Artificial Intelligence (AI) and Machine Learning (ML). He is one of the most prominent researchers world-wide in the field of Quantum Computation.
Dr. Ganz's articles and breakthroughs have been published in world-renowned scientific publications & journals.
He has been heading Urecsys' Machine Learning Department for 6 years, acted as the Chief Technology Officer, and has led much of the research into air pollution kinetics and behaviour in real-time.

Some Publications:
A simpler proof of existence of quantum weak coin flipping with arbitrarily small bias, SIAM Journal on Computing · 2016
Quantum leader elections, Quantum Information Processing · 2017
Quantum coin hedging, and a counter measure, LIPICS · 2017
Dining Philosophers, Leader Election and Ring Size problems, in the quantum setting, AQIS 2017

Some of the key talks:
Asian Quantum Information Science Conference, Singapore 2017
Facility Management Expo 2022
Bynet Leading with EmPassion, collaborating with AI, Expo 2023
Bynet EXPO-2022 Empowering Growth

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