Creation big data analytical-recommender method and system for safe and healthy housing

Abstract

European citizens more than 90 percent. time spent indoors. More than 40 per cent. people complain about indoor health and comfort. Outdoor and indoor air pollution can cause respiratory and cardiovascular diseases, cancer, premature birth and infant mortality rate increased, neurological and psychiatric disorders, impair immunity and haematological features. Therefore, it is essential to create healthy buildings and their environment and improve the quality of life for residents in housing. Ensuring a life quality in house could increase productivity, reduce morbidity and healthcare costs. In order to predict and reduce the negative impact, it is necessary carry out extensive analysis of the big data. Big data analysis could provide a safe and healthy housing guidance system (Big Data Housing Health and Safety Recommender System, HOSS), allowing interested parties to contribute a safe and healthy housing and preserve the good health. In article is presented the public administration institutions' role in creating a safe and healthy housing big data analytical-recommender system. Analyzes the recommender system design capabilities applying human relations management and organizational theory (systems management, quantitative management), psychological and quantitative management methods.