Work

Design and Deployment of a Multi-Modal Multi-Node Sensor Data Collection Platform

Year: 2022

Type: conference-paper

Abstract: Sensing and data collection platforms are the crucial components of high-quality datasets that can fuel advancements in research. However, such platforms usually are ad-hoc designs and are limited in sensor modalities. In this paper, we discuss our experience designing and deploying a multi-modal multi-node sensor data collection platform that can be utilized for various data collection tasks. The main goal of this platform is to create a modality-rich data collection platform suitable for Internet of Things (IoT) applications with easy reproducibility and deployment, which can accelerate data collection and downstream research tasks.

Source: ACM Conference on Embedded Networked Sensor Systems (SenSys)

DOI: 10.1145/3560905.3567770

Authors: Shiwei Fang, Ankur Sarker, Ziqi Wang, Mani Srivastava, Benjamin Marlin, Deepak Ganesan

Institutions: University of Massachusetts Amherst, University of California System

Language: English

Topic: Arduino and IoT Applications

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: bronze

Funder: U.S. Department of Defense