Urban Internet of things (Urban IoT) will play a vital role in our daily lives to achieve the concepts of smart cities, urban brains, etc., by handling continuously generated data from sensors deployed in the city. However, the unprecedentedly large amount of sensing data generated also brings challenges for Urban IoT, i.e. how to offload these sensing data to suitable processing facilities and provide high-quality services.

Sensors and devices are usually resource-constrained and heterogeneous in that the communication, computing, storage, and battery capacities are differing and limited. Additionally, the architecture of urban IoT is also sophisticated in that the urban IoT service usually processes sensing data from different kinds of sensors and devices depending on its requirement and guaranteeing the quality of experiences, devices are equipped with different communication modules. To improve the quality of urban IoT services, many efforts have been made from both academia and industry to study frameworks, architectures, mechanisms, and algorithms for effective data offloading of urban IoT, such as integrating edge/fog computing frameworks, mobile crowdsourcing, next generation communication technologies (i.e. 5G, 6G, etc.), AI-enabled algorithms, and others. Nonetheless, there is still much progress to be made before deploying the concept of urban IoT in practice.

The goal of this Special Issue is to collate articles with a focus on challenging issues in the field of data offloading frameworks, technologies, algorithms, frameworks, architectures, and applications for urban IoT services. Both theoretical and experimental contributions containing novel applications with new insights and findings in the field of Urban IoT are welcome. Review articles which detail the current state of the art are also welcome.

Potential topics include but are not limited to the following:

• Emerging advanced data offloading techniques, frameworks, and algorithms for urban IoT
• Edge/fog computing framework for data offloading for urban IoT
• Next generation wireless communication technologies for data offloading for urban IoT
• Data collecting, communicating, and processing mechanisms/algorithms for urban IoT
• Crowdsourcing-enabled data offloading techniques for urban IoT
• Data offloading in heterogeneous network scenarios for urban IoT
• AI-enabled techniques for data offloading for urban IoT
• Data offloading mechanisms for resource-constrained urban IoT
• QoE-aware data offloading mechanisms for urban IoT services and applications
• Other innovative techniques for urban IoT data offloading