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Experimental results obtained from a network of sensor nodes utilizing the proposed architecture and the application-layer protocol reveal that this novel approach is suitable for effectively communicating multimedia data over wireless sensor networks.
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In order to utilize the proposed architecture, WSN developers have to design various types of autonomous event handlers for different subtasks of their specific WSN applications.
By utilizing multiple Stream-IN PEs, the proposed architecture allows multiple transmitters to send data at different data rates and carrier frequencies.
The proposed architecture utilizes a single degree-of-freedom (DOF) drive-mode and a fully coupled 2-DOF sense-mode.
The proposed architecture utilizes the 100% capacity of FPGA's dedicated Block RAM (BRAM) as compared to conventional techniques, where the consumption of BRAM memory is from 25%to50%0%.
The proposed architecture utilizes structurally decoupled active-passive mass configuration to achieve dynamic amplification of oscillation in 2-DoF drive-mode.
The proposed architecture utilizes the concept of binary classification of SVM (Support Vector Machine) and the concept of multiclass classifier of Neural Network to identify the SPAM and category of the data received online.
The proposed architecture utilizes a Multi-Agent System (MAS) for the realization of an Integrated Oil Pipeline Monitoring and Incident Mitigation System (IOPMIMS) that can effectively monitor and provide actionable information for pipelines.
The proposed architecture also utilizes IPsec tunnels to secure the SDMN communication channels by eliminating these limitations.
Unlike its counterparts that utilize piezoelectric cylinders for fiber actuation, the proposed architecture offers quasi-static actuation in the axial direction along with resonant actuation in the lateral directions forming a 3D scanning pattern, allowing adjustment of the focus plane.
We also utilized consistent datasets on the Hadoop server to validate the proposed architecture based on threshold limit values (TLVs).
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