The increased deployment of Internet of Things (IoT) devices in this decade has created a body of new application domains, such as ambient intelligence, industrial control and monitoring systems, assistive living, smart meteorology, intelligent surveillance, cyber physical systems, and high performance IoT networks. These applications generate huge amounts of data every day, and with the rapid development of computer science and artificial intelligence, a variety of these methods have been introduced into this field with success.

While many current methods assume good and clean data as inputs, in real applications, the data are usually from several sources, heterogeneously styled, imperfect, and possibly inconsistent, due to reasons such as inaccurate, tampered, or malfunctioning sensors or inaccurate data preprocessing. In addition, the data may be spread over a wide temporal and spatial range, part of which could be missing. These problems make it difficult to process imperfect real data in an integrated way to find useful patterns.

The aim of this Special Issue is to help researchers and practitioners to disseminate, exchange, and discuss all recent advances related to data processing techniques involving imperfect real data from IoT environments. Our Special Issue is intended to present high quality original research or review articles focused on all areas related to intelligent processing approaches applied to various IoT environments with imperfect data.

Potential topics include but are not limited to the following:

• Machine learning and deep learning applications in meteorology, such as precipitation nowcasting, hurricane and drought forecasting, hail size classification, and thunderstorm prediction
• Knowledge representation and reasoning applications in intelligent surveillance, such as bus station monitoring, city crime spotting and prevention, and airport corridor surveillance
• Natural language processing applications in smart homes and social networks, such as assistive living, people and organization identification, and sentimental analysis
• Big data applications in Internet of Things and wireless networks, such as ad hoc swarm analysis, mobile edge computing, and visual simultaneous localization and mapping