Abstract
Thanks to technology advances, large-scale WSNs and mobile WSNs are now more affordable than ever, and WSNs may be useful in many different applications. Many current wired sensor systems in industry are used to monitor lumped parameter systems such as electrical motors. Replacing the wired systems by WSNs can be very attractive, because wireless systems are much easier to install and maintain. In addition, if we deploy a larger number of wireless sensors, the system may be more robust against sensor failures. However, WSNs are not simple replicas of their wired counterparts. There exists a wide class of processes whose behaviors are described by PDEs due to the inherent spatial and temporal variability of their states. These are commonly referred to as DPSs. Since parameters of a DPS are, as the name suggests, distributed, it makes sense to deploy many sensors to measure the parameters at many different positions. This many result in a fine grid and more precise observation than traditional wired sensing systems, which are normally much smaller in scale due to the difficulties of wired connections. Thus, it may be useful to apply WSNs in a variety of scenarios, including the following applications:
• Wildfire monitoring [4]
• Landslide prediction [106]
• Volcano status monitoring [35]
• Diffusive pollution monitoring and control [84, 85]
• Water pollution monitoring [24]
• Chemical plume tracking [107]
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© 2009 Springer London
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(2009). Mobile Sensor Trajectory Optimization. In: Optimal Observation for Cyber-physical Systems. Springer, London. https://doi.org/10.1007/978-1-84882-656-4_2
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DOI: https://doi.org/10.1007/978-1-84882-656-4_2
Publisher Name: Springer, London
Print ISBN: 978-1-84882-655-7
Online ISBN: 978-1-84882-656-4
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