Sustainable Smart Aquaponics Farming Using IoT and Data Analytics

IoT Data Analytics Using Deep Learning

Xiaofeng Xie, Di Wu, Siping Liu, Renfa Li Abstract: Deep learning is a popular machine learning approach which has achieved a lot of progress in all traditional machine learning areas. Internet of thing (IoT) and Smart City deployments are generating large amounts of time-series sensor data in need of analysis. Applying deep learning to these domains has been an important topic of research. The...

Real-Time IoT Stream Processing and Large-scale Data Analytics for Smart City Applications

Data Compatibility to Enhance Sustainable Capabilities for Autonomous Analytics in IoT

The collection of raw data is based on sensors embedded in devices or the environment for real-time data extraction. Nowadays, the Internet of Things (IoT) environment is used to support autonomous data collection by reducing human involvement. It is hard to analyze such data, especially when working with the sensors in a real-time environment. On using data analytics in IoT with the help of RD...

Streamlining Smart Meter Data Analytics

Today smart meters are increasingly used in worldwide. Smart meters are the advanced meters capable of measuring customer energy consumption at a fine-grained time interval, e.g., every 15 minutes. The data are very sizable, and might be from different sources, along with the other social-economic metrics such as the geographic information of meters, the information about users and their proper...

Smart Aquaponics System: Challenges and Opportunities

Aquaponics, despite their name, pose a revolutionary change to the organic agriculture field. The world is facing a number of serious issues of which climate variation, population rise, water scarcity, soil degradation, and food security are among the most significant. Aquaponics, as a closed loop system consisting of hydroponics and aquaculture elements, could contribute to addressing these is...