Emnotion 2016
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The document discusses developing technology to better understand city climates through dense weather monitoring networks. It notes that current climate data sources have low-resolution data at the city level. The document proposes installing a network of properly placed weather stations in cities to collect high-quality local climate data. It describes using artificial intelligence techniques like machine learning and neural networks to analyze the data and model urban climates. This could provide benefits like improved routing, emergency planning, health monitoring, and energy use prediction at the street level. The document outlines a plan to pilot the approach in Batumi, Georgia and release apps using the collected data and models.
Emnotion 2016
- 2. Alex Graduated the Tel Aviv University, Plant Biology / Ecology department, J-Group-Global Company (Israel) Research and Development Manager, UNDP Turkmenistan Resilience and Climate Change expert, Emnotion Company co- founder and R&D officer. “Choose the profession that you love – and you will not have to work even a day in your life”. Ilya BSc Eng, MBA, co-founder and CEO of the group of companies’ - ‘J Group Global Ltd’ ‘Isragreen LLC Georgia’ ‘Your Forest Foundation NPO Georgia’, ‘Emnotion LTD Israel’, ‘J Group Global Turkmenistan’. Believing that systematic and scientific approach and strongly professional team are the keys to any success endeavors. OUR TEAM Sahara Project manager Alexandr GIS specialist, Cartography, Geoinformatics Marina Designer Ksenya Software developer Sergey C/C++ Software developer
- 3. ‘’Globally, more people live in urban areas than in rural areas, with 54 per cent of the world’s population residing in urban areas in 2014. By 2050, 66 per cent of the world’s population is projected to be urban.’’ ‘’Continuing population growth and urbanization are projected to add 2.5 billion people to the world’s urban population by 2050, with nearly 90 per cent of the increase concentrated in Asia and Africa.’’ According to UN GLOBALY BY 2050 ‘’As the world continues to urbanize, sustainable development challenges will be increasingly concentrated in cities, particularly in the lower-middle-income countries where the pace of urbanization is fastest. Integrated policies to improve the lives of both urban and rural dwellers are needed. ‘’
- 4. The severe European heatwave of 2003 had wide ranging impacts on public health, the economy, infrastructure, and ecosystem health. The effects were particularly noticeable in northern and central Europe, where it has been estimated that up to 70,000 excess deaths were associated with the heatwave in August 2003. France was particularly affected, with an estimated 14,802 excess deaths reported, 2,085 of which were in the city of Paris, and high night time minimum temperatures were associated with increased mortality in the centre of Paris. In England, the Office for National Statistics (ONS) estimated that 2,091 excess deaths were associated with the heatwave, of which, 616 were estimated for London. The highly urbanised region of the West Midlands, the focus of this study, had an estimated 130 excess deaths during the heatwave period. http://www.climatechangenews.com/
- 5. • Smart Light • Smart Traffic • Smart CCTV • Smart Pollution Detection • Smart Parking • Smart Delivery by drones • Smart Electric cars • Smart Health monitor SMART CITY TODAY It is obvious there are big challenges in face of urbanization and population growth. That is why SMART CITY approach is so important and many try to be involved – business and government. BILLIONS OF DOLLARS INVESTED IN IFRASTRUCTURE AND EQUIPMENT
- 6. Weather DATA and service suppliers today Todays climatic DATA and predictions are based mostly on Space Satellites and ground stations. There are 2 basic problems: 1. Satellites – low resolution at ground level and highly influenced by cloudiness 2. Ground stations – most of them do not installed in proper way and have high level of variance.
- 7. It will be very hard for • pedestrian – temperature, winds, humidity, barometric pressure, UV, heatwaves • drone delivery – winds and temperatures • skyscrapers architects – temperatures, humidity, UV and winds • healthcare – winds, humidity, temperature, UV • energy consumption – winds, UV and temperatures • flying transport - winds, humidity and temperatures • pollution - winds, humidity and temperatures BUT NO WORD ABOUT CITY CLIMATE! We live in era when the new technologies are coming too fast and somewhere we lose the basic – physics and math beneath this. to be sustainable without deeper understanding of physics – climate into-city
- 8. 1. Cause apparently from other issues, climate based correlations must be done by using the reliable data that comes from properly installed measurement equipment Not from nearby airport Not from neighbor private station Not from 30000 km satellite It must come from city’s weather stations net 2. Cause we will deal with aerodynamics and thermodynamics in large scale. 3. Cause the Mother Nature multiplied by urban disorder is something really hard to deal with. THIS IS REAL BIG DATA! BUT Once you can manage it, lots of interesting thing will happen! REASONS So, why so little are done if so, and mainly on academic level, for better understanding of - city climate?
- 9. - The Structure and Semantic of Text Technology matching, which is distinguished by requirements absence at the initial education stage and language independence; - The Technology to determine the main meaning and sub meanings of the Text. - The Technology for creating the Category Tree of user interests and documents, which is distinguished by constant (determined by the System Administrator) and liberally variable (defined by User’s desire) parts of the Category Tree; - The Estimation Technology of User actions, which is distinguished by the User actions types and methods of its estimation. - The Quality Estimation Technology of User own documents and expertise of User skills of collective opinion usage. The foundations of Artificial Intelligence software are five technologies
- 10. ATE - The associative transformation engine The basis of this engine is look for the structure identical and semantic close texts; DF - Dynamic filter Determine main meaning and sub meanings of text. DCE - The dynamic category engine (dynamic optimal categorization of the information space) The dynamic change of the category tree structure; The forming and the dynamic change of the subcategories names; The Technologies are based on six general engines:
- 11. UDIE – The user distribution information engine (dynamic optimal structure of the information space) The grouping, expansion and prediction of the member interests; Distribution of the user information; UIAE - The user information activity engine The dynamic forming user groups; The optimization of the information activity user process; DEE – The dynamic estimate engine The algorithms of the dynamic estimate user activity, categories and information; The algorithms of the measure popularity determination for the structure texts fragments and for users The Technologies are based on six general engines:
- 12. How we use AI for our decisions? 1.Step one: Machine learning for establishing smart multi-level clusters. Step two: Modeling Urban Artificial Neural Networks using our engines. Step three: Create ecological model and dynamics of urban area based on artificial neural network
- 13. WHAT FOR? BASED ON 3D CLIMATE MAPPING = City DNA WE WILL BE ABLE TO: 1. Smart route based on climate DATA for a. Pedestrians – sport, shopping, pleasure based on mobile application b. Drones – safer and faster delivery c. Municipal – evacuation routes in case of disaster d. Business – delivery, transportation, tourists, advertisement along routes 2. Recreation – crowd events 3. Health – disease distribution and localization in correlation with Med DATA 4. Flooding prediction by street resolution 5. Heat/Cold wave prediction by street resolution 6. Energy – energy consumption prediction by street resolution 7. Building – shape and location influence on future neighbor’s climate 8. Pollution – distribution by street resolution based on pollution sensors correlated with climate DATA 9. Better prediction for energy derivatives. 10. Future correlations with other DATA for new indicators
- 15. Financial Aspect There are 2 different approaches to commercialize this project: 1. Sell services and DATA from established weather stations net. a. Ads b. Weather DATA c. Routing for private sector based on mobile app 2. Sell as turn-key project to investors or officials Budget will depend on city size and complicity.
- 16. What we have now? Summer 2016 we installed small weather stations net in Batumi (Georgia) for evaluation of our approach and algorithms - 7 weather stations. June 2017 we plan to release first version of Urban App. Based on the same approach we are going to release first version of Rural and Agro Emnotion as a solution for clustering and monitoring climate of rural areas.
- 17. THANK YOU!