Structural Health Monitoring Using Smart Sensors - ideals ...

Modal operation
Several modal operations for the microprocessor, such as sleep, watchdog, and
awake, facilitate a resource-efficient operation. For example, following a preprogrammed
schedule, nodes enter the watchdog mode to save power. When no significant event to
observe is expected, the nodes go into the sleep mode. The smart sensors should be able to
transition from one operation mode to another, depending on the tasks to be achieved.
2. Autonomous distributed embedded computing
Model-based data aggregation
The data measured at nodes should be processed locally so that a reduced amount of
data needs to be sent throughout smart sensor networks. Data size reduction without data
degradation should be sought. Algebraic operations such as averaging, numerical filtering,
and resampling, are simple examples. More complex mathematical manipulation such as
frequency analysis may better compress information. Data aggregation based on
knowledge or insight on a structural system is expected to further condense measured data
without compromising the structural information contained. Ideally, only necessary and
sufficient information for the task is transmitted throughout networks.
Collaborative distributed data processing
Distributed data processing eliminates the problem of having a single point of failure
and balances the power consumption among nodes. Also, distributed processing offers
efficient computation, which can be much faster than centralized processing. Distributed
processors, accompanied by cache memory and RAM, contribute to fast computation.
Although resources on each node are limited, sensor networks as a whole possess
appealing computational capabilities.
Autonomous initial configuration and maintenance
The network topology is desired to be dynamically and autonomously configurable.
When smart sensors are physically installed, the sensor nodes need to construct a network
and configure the topology. Because node loss is likely to take place, network
configuration should be adjusted autonomously so that loss of a single node does not take
the system down. Autonomous reconfiguration also allows balancing power consumption
among sensor nodes by switching relay nodes on multihop communication paths.
Individual nodes should be reconfigurable through the network as well. For the initial
set up of a smart sensor network, a large number of nodes need to be programmed as well
as physically mounted. In the long term, the nodes may need to be reprogrammed to
implement different tasks or to reschedule the tasks. Smart sensors are desired to be
programmable through the network, because manual reprogramming of thousands of
nodes is too time consuming and error prone.
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