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Another aspect of increasing importance, and strongly linked to data processing and the amount of data available concerning processes or devices (due to the high level of sensors and monitoring), is the extraction of knowledge from data to discover the information structure hidden in it.
Integrating it all, from the lowest hardware level of sensors and actuators, via the level of networked PLCs and computer systems, up to functions and classes in programming languages, demands a sound and modular software architecture, which is extendable and scalable for future changes.
This is perhaps in two areas, the level of sensors and data collection is now rapidly increasing from mobile phones, security cameras to devices in the home like Amazon Echo and Google Home starting to record huge amounts of data about our behavior and choices.
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E. Ibarra et al. [38] exploit energy harvesting with considering energy level of sensor nodes.
(mathcal {A}_{i}) is the available energy level of sensor node i considering the recharging with the energy harvester.
In order to balance the network energy consumption, we dynamically adjust the transmit power level of sensor nodes based on their remaining energy.
Simulation results show that STKM is very resilient to node compromise while preserving energy consumption at the level of sensor nodes.
Actually, sensing redundancy can be exploited to enhance the attainable availability level of sensor networks, since redundant nodes can replace faulty nodes.
In this work, after treating the bioselective element with bound IgG with 40 mM sodium citrate buffer (pH 2.5) [27], the level of sensor signal almost backs the values that preceded the IgG injection (Fig. 3).
In WSNs, sensors are usually equipped with capacity-limited battery sources that can sustain longer or shorter period, depending on the energy usage pattern and the activeness level of sensor nodes.
The quantity that used for energy-balancing evaluation is the energy variance over all nodes which calculated as follows: nu = frac{1}{n}sum_{i=1}^{n} (mathcal{A}_{i}- overline{mathcal{A}})^{2} where (mathcal {A}_{i}) is the energy availability level of sensor node i after the allocation and (overline {mathcal {A}}) is the mean value.
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