IoT Data Sink Commissioning via Weighted Source Prioritization
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Solution Overview
Problem
Existing IoT-network configurations require manual labor and are static, necessitating manual updates for network changes, which is inefficient and error-prone.
Innovation Solution
An automated method and IoT-data sink device that prioritizes IoT-data source devices based on location and data quality attributes using a prioritization algorithm to dynamically manage network structure changes, reducing manual effort and ensuring flexible data sourcing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration methods are used to manage IoT-device relationships, then configuration accuracy can be maintained, but labor costs increase and adaptability to network changes deteriorates
Solution Approach 1:
The system enables automated self-configuration of IoT devices through a broker device that autonomously discovers data sources, computes proximity metrics, and establishes data connections without human intervention. The broker device automatically manages network structure changes by detecting new devices, calculating weighted proximity based on location and data quality, and configuring data flow relationships dynamically.
Solution Approach 2:
The configuration system transitions from static manual setup to dynamic automated management. The broker device continuously monitors network changes, recalculates proximity metrics when devices are added or removed, and dynamically adjusts data source-sink relationships. This allows the system to adapt automatically to network structure changes while reducing manual operational requirements.
2Adaptability or versatility
If static configuration is used before device commissioning, then initial setup can be completed, but the configuration cannot adapt to dynamic network changes
Solution Approach 1:
A broker device is introduced as an intermediary between IoT data sources and data sinks. The broker automatically discovers available data sources, computes proximity metrics considering location and data quality attributes, and manages data flow routing. This intermediary handles the complexity of dynamic configuration management, allowing individual devices to operate with simpler local configurations while the broker adapts to network changes centrally.
Solution Approach 2:
The system performs preliminary automated configuration actions during device commissioning. When new IoT devices join the network, the broker device automatically detects them, computes their proximity to relevant data sinks, and establishes appropriate data connections without requiring manual configuration. This preliminary automated setup enables dynamic adaptation while reducing operational complexity.
3Adaptability or versatility
If hardware solutions with physical connections are used, then connection reliability is improved, but flexibility and ease of reconfiguration deteriorate
Solution Approach 1:
The system replaces physical hardware connections with wireless communication and software-based data routing. The broker device manages logical connection relationships between data sources and sinks through network communication, eliminating the need for physical cabling. This substitution provides reconfiguration flexibility through software while maintaining connection reliability through protocol-level error handling and automatic connection management.
Data Source
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AI summary
In order to manage network structure changes of an IoT-network (NWIoT) with at least one IoT-data source device (DSODIOT,1, DSODIoT,2), in which the network structure changes are managed automatically and in which the network structure is changeable due to commissioning of an IoT-data sink device (DSIDIoT) within the IoT-network (NWIoT) by configuring the IoT-data sink device to be commissioned or by adapting or retiring and replacing current data of the IoT-data sink device, it is proposed to (i) prioritize (prt) information about a location (INFloc) of the IoT-data source device and information about quality attributes of IoT-data source device data (INFdqa), being sourced by each IoT-data source device and being requested (req) and fetched (ftc) from each IoT-data source device, via a communication link (COL) with a prioritization algorithm (PRA) such that - a weighted proximity metric is computed (cpt) for each IoT-data source device according to which a weighted proximity is computed based on the location information and which takes into account the data quality attribute information, wherein weights for each input parameter of the prioritization algorithm is pre-configured for the IoT-data sink device, - each IoT-data source device is ranked (rnk) according to the weighted proximity computed for the IoT-data source device, and (ii) to select (slc) the IoT-data source device ranked highest, from which its IoT-data source device data is fetched via the communication link (COL) and wherein the fetched is used to configure the IoT-data sink device due to its commissioning or to adapt or retire and replace current IoT-data sink device data of the IoT-data sink device.