Towards convergence of AI and IoT for energy efficient communication in smart homes

The convergence of Artificial Intelligence (AI) and Internet of Things (IoT) promotes the energy efficient communication in smart homes. Quality of Service (QoS) optimization during video streaming through wireless micro medical devices (WMMD) in smart healthcare homes is the main purpose of this research. This paper contributes in four distinct ways. First, to propose a novel Lazy Video Transmission Algorithm (LVTA). Second, a novel Video Transmission Rate Control Algorithm (VTRCA) is proposed. Third, a novel cloud-based video transmission framework is developed. Fourth, the relationship between buffer size and performance indicators i.e., peak-to-mean ratio (PMR), energy (i.e., encoding and transmission) and standard deviation is investigated while comparing the LVTA, VTRCA, and Baseline approaches. Experimental results demonstrate that the reduction in encoding (32%, 35.4%) and transmission (37%, 39%) energy drains, PMR (5, 4), and standard deviation (3dB, 4dB) for VTRCA and LVTA, respectively, is greater than that obtained by Baseline during video streaming through WMMD

Energy consumption analysis of high quality multi-tier wireless multimedia sensor network

Abstract Video surveillance is one of the promising applications of the Internet of Things paradigm. We see heterogeneous deployment of sensor platforms in a multi-tier network architecture as a key enabler for energy optimization of battery powered high-quality video surveillance applications. In this paper, we propose a heterogeneous wireless multimedia sensor network (WMSN) prototype composed of constrained low-power scalar sensor nodes and single board computers (SBCs). Whereas constrained nodes are used for preliminary motion detection, more capable SBCs are used as camera nodes. The camera nodes stream full HD (1080 pixels) video to a remote laptop during occurrence of an event (when motion is detected). We also present a simple power model and simulation results of battery life of the motes for variable event interval and event duration