Arav Yehuda, Klausner Ziv, David-Sarrousi Hadas, Eidelheit Gadi, Fattal Eyal
Department of Applied Mathematics, Israel Institute for Biological Research, P.O. Box 19, Ness-Ziona 7410001, Israel.
Sensors (Basel). 2024 Sep 12;24(18):5916. doi: 10.3390/s24185916.
Information and decision support systems are essential to conducting scientific field campaigns in the atmospheric sciences. However, their development is costly and time-consuming since each field campaign has its own research goals, which result in using a unique set of sensors and various analysis procedures. To reduce development costs, we present a software framework that is based on the Industrial Internet of Things (IIoT) and an implementation using well-established and newly developed open-source components. This framework architecture and these components allow developers to customize the software to a campaign's specific needs while keeping the coding to a minimum. The framework's applicability was tested in two scientific field campaigns that dealt with questions regarding air quality by developing specialized IIoT applications for each one. Each application provided the online monitoring of the acquired data and an intuitive interface for the scientific team to perform the analysis. The framework presented in this study is sufficiently robust and adaptable to meet the diverse requirements of field campaigns.
信息与决策支持系统对于开展大气科学领域的科学考察活动至关重要。然而,其开发成本高昂且耗时,因为每次实地考察都有其自身的研究目标,这导致使用一套独特的传感器和各种分析程序。为了降低开发成本,我们提出了一个基于工业物联网(IIoT)的软件框架,并使用成熟的和新开发的开源组件进行实现。这种框架架构和这些组件使开发人员能够根据考察活动的特定需求定制软件,同时将编码量降至最低。通过为两个涉及空气质量问题的科学实地考察活动开发专门的工业物联网应用程序,对该框架的适用性进行了测试。每个应用程序都提供了对采集数据的在线监测以及供科学团队进行分析的直观界面。本研究中提出的框架足够强大且适应性强,能够满足实地考察活动的各种需求。