ABSTRACT
An Internet of Things (IoT) platform with capabilities
of sensing, data processing, and wireless communication has been deployed to
support remote aquatic environmental monitoring. In this paper, the design and
development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the
spatiotemporal quality evaluation of surface water is presented. A survey planner
is proposed to distribute the Sampling Locations of Interest (SLoIs) over the
study area and generate paths for MSNs to visit the SLoIs, given the limited
energy and time budgets. The SLoIs are chosen based on a cellular decomposition
that is composed of uniform hexagonal cells. They are visited by the MSNs along
a path ring generated by a planning approach that uses a spanning tree. For quality evaluation, an Online Water Quality Index
(OLWQI) is developed to interpret the large quantities of
online measurements.The index formulations are
modified by a state-of-the-art index, the CCME WQI,
which has been developed by the Canadian Council of
Ministers of Environment (CCME) for off-line indexing.
The proposed index has demonstrated effective and
reliable performance in online indexing a large volume
of measurements of water quality parameters.
The IoT platform is deployed in the field,
and its performance is demonstrated
and discussed in this paper.
PROBLEM   STATEMENT