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Found 4 papers, 0 papers with code
A Deep Reinforcement Learning Approach for Composing Moving IoT Services
We develop a novel framework for efficiently and effectively discovering crowdsourced services that move in close proximity to a user over a period of time.
Drone-as-a-Service Composition Under Uncertainty
Specifically, we propose a service model of DaaS based on the dynamic spatiotemporal features of drones and their in-flight contexts.
Cognitive Amplifier for Internet of Things
We present a Cognitive Amplifier framework to augment things part of an IoT, with cognitive capabilities for the purpose of improving life convenience.
A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services
This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally.
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