Sofia Air Pollution Case Team BG-USA: Kristiyan Vachev – Bulgaria () Sergey Vichev – Bulgaria () Stefan Panev – Bulgaria Georgi Kirilov – Bulgaria Mike Lane – USA () Data Preparation Geocoding the construction data: The original source file can be found here. Basically, this is very very similar to geocoding as proposed in the original documentation […]
Sofia is a city with significant concentrations of particulate matter less than 10 micrometers in diameter (PM10.) A high concentration of PM10 is disruptive to life and the climate. The purpose of this project is to predict the concentration of PM10 at a particular day given the climatic conditions. This is important in allowing the making of policies to reduce the pollution in the city. Our contribution consists of a random forest regressor that acheives the purpose with 70 to 80% accuracy.
Dear participants, you rock 🙂 Please be open, friendly, fancy and collaborative. We are not perfect but let’s learn together through the long way of Data Science. Here are some instrucions and guidelines which you can refer to. Our objectives during the event are to have fun, learn, share and make friendships and meanwhile if […]
Sofia Air 2.0 A study to investigate the static factors that are affecting the air pollution levels Note: Due to the high methodological complexity and the sheer size of the data the experts’ team authoring this case decided to postpone the traffic data for one of our next cases. So, the current case (which is […]
Sofia Air Case 2.0 (Level 1) Business Understanding: Sofia, the Capital city of Bulgaria, is a center of attention when it comes to pollution levels on European grounds. The poor citizens have been suffering from a polluted atmosphere reigning over the city. Sofia Air Case 2.0 aims to pinpoint what factor is affecting that pollution […]
Overview Our approach to the problem is as follow: Data Augmentation – in the data augmentation phase we are creating synthetic images based on the dataset we have. This helps us to have larger dataset for model training and validation Object detection – There are several challenges with the object detection. First, sample is imbalanced […]
GitHub Accounts: KarimEid1, Marcel344, scopyro , @boudy87
Air pollution is quite a topic today. The municipality is investing a lot of effort and resources in order to measure the exact values of the gases and particulate matter in the air in order to identify its quality.
This is the next step towards the completion of a story and holistic view over the data-driven and explained the social topic of unveiling the secrets behind the information about Sofia Air Quality.
This research differentiates the main sources of pollution in Sofia and tries to predict what are the growing rate of this pollution in order to rise awareness against this danger and visualize, in numbers, its growth rate.
1. Business Understanding A Kaufland store is a very big thing. It has a sales floor of up to 12.000 square meters and provides more than 30.000 products. A lot of events can occur on our shelves that are likely to be overlooked. Items can get sold out, other items might be placed on the […]
Case Summary A Kaufland store is a very big thing. It has a sales floor of up to 12.000 square meters and provides more than 30.000 products. A lot of events can occur on our shelves that are likely to be overlooked. Items can get sold out, other items might be placed on the wrong […]