Many countries are concerned about high particulate matter (PM) concentrations caused by rapid industrial development, which can harm both human health and the environment. To manage PM, the prediction of PM concentrations based on historical data is actively being conducted. Existing technologies for predicting PM mostly assess the model performance for the prediction of existing PM concentrations; however, PM must be forecast in advance, before it becomes highly concentrated and causes damage to the citizens living in the affected regions. Thus, it is necessary to conduct research on an index that can illustrate whether the PM concentration will increase or decrease. We developed a model that can predict whether the PM concentration might increase or decrease after a certain time, specifically for PM2.5 (fine PM) generated by anthropogenic volatile organic compounds. An algorithm that can select a model on an hourly basis, based on the long short-term memory (LSTM) and artificial neural network (ANN) models, was developed. The proposed algorithm exhibited a higher F1-score than the LSTM, ANN, or random forest models alone. The model developed in this study could be used to predict future regional PM concentration levels more effectively.

The Internet of Things (IoT) and blockchain technologies characterizing the era of the fourth industrial revolution have enabled smart home networks to support their various systems and services. In a blockchain-based smart-home network environment, all connected IoT devices must be controlled safely and efficiently. Nevertheless, existing block-chain-based smart-home IoT systems pose a delay issue due to the necessary block generation time. In addition, IoT devices installed in smart homes should be able to prevent forgery attacks such as spoofing because they are often directly associated with personal information. In this study, we proposed an enhanced method to control smart home devices safely and efficiently by applying the zero-knowledge proof combined with a blockchain-based IoT system to protect the public keys of home network devices and the communication among them. The proposed model was approximately 10 s faster than the block generation-based model when it communicated three times in rinkeby, which is one of the test networks of Ethereum.