Gathering Contextual Data with Power Information Using Smartphones in Internet of Everything

Abstract

The advent of smart devices, interacting with each other as well as remote services, has paved the way for the Internet of Everything (IoE). IoE is a direct successor of Internet of Things (IoT), composed of smart devices interacting with remote services. The devices in an IoE environment are power constrained. At the core of an IoE environment, there is a context-aware system that gathers the context and classifies it. Various datasets have been published by authors for context-aware systems. This paper presents a mechanism that gathers a dataset of contextual information along with power information using smartphones. An Android application “PowerIpsum” is developed for gathering contextual information, power information, and user input activity labels. The dataset includes the sensor data as the contextual data, timestamps, average current, and average voltage as well as user activity labels. Time elapsed and power consumption is forecasted using Monte Carlo method. The results provide useful insights and demonstrate the advantages of power information within a context-aware system.

A Distributed Emergency Vehicle Transit System Using Artificial Intelligence of Things (DEVeTS-AIoT)

“…The sleep mode would let reduce power consumption over a 24-hour period. For an adaptive sleep-scheduling mechanism, a dataset must be compiled after deployment [55].…”