These analytical bounds couple the physical quantities of interest to facilitate planning the motion of the mobile sensors for minimizing the probability of missed detection.
This study proposes to explore how the inclusion of mobile sensors for inline monitoring of various water quality parameters (e.g., residual chlorine, pH) can enhance water distribution system security.
Major milestones include the automated control of multiple, mobile sensors for weeks using spatial coverage metrics and the transition from engineering a reliable data stream to managing the complexities of decision-making based on the data and the possibilities of timely feedback.
Given this study design, mobile measurements of PA and exposure to TRAP are necessary; a number of previous studies managed to use new mobile sensors for this [ 34, 35].
Use of node mobility in mobile sensor networks for relocation after initial random placement was previously suggested in [11, 12].
Here we introduce the Canopy-Meter – a mobile sensor designed for determining LAI while driving over the field.
The t-ANOCOVA approach requires further validation before real-world implementations, but represents a significant step towards the use of ECa mobile sensor technology for inexpensive soil salinity monitoring at high temporal resolution.
There are several means of obtaining information about the plants health, including manual data collection from sensors installed in the soil and/or its vicinity, mobile sensor systems, for example embedded sensors in UAVs, or aircrafts, or other vehicles, and satellite imagery, to name just a few examples.
Wang et al. proposed saluting of scheduling mobile sensor and fixed sensors for target tracking algorithm.
In this paper, we consider the cluster-based architecture and provide distributed clustering algorithms for mobile sensor nodes which minimize the energy dissipation for data-gathering in a wireless mobile sensor network.
