Self-Configuring Sensor Network for Industrial IoT Reliability
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Solution Overview
Problem
Industrial IoT systems face challenges in industrial settings due to communication issues with cellular and Wi-Fi protocols, bandwidth strain, security vulnerabilities, and the need for complex integration and deployment, deterring organizations from adopting IoT solutions.
Innovation Solution
A self-configuring sensor kit network with edge computing devices and machine-learned models that automatically provision and manage sensor data transmission, using various communication protocols and gateways to efficiently transmit data to backend systems while addressing security and integration complexities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cellular or Wi-Fi protocols are used for communication in industrial settings, then network connectivity is provided, but communication reliability deteriorates due to heavy machinery and thick dense structures affecting signal transmission
Solution Approach 1:
The patent introduces a mesh network topology where sensors act as intermediaries to relay data to each other and to the gateway. This mesh network serves as an intermediary communication path that bypasses the need for direct line-of-sight communication with external networks, thereby overcoming signal obstruction from heavy machinery and dense structures.
2Quantity of substance
If hundreds or thousands of sensors are deployed to capture multiple readings every second, then data collection capability is improved, but bandwidth strain increases putting pressure on computing resources
Solution Approach 1:
The patent segments the data processing function by introducing edge computing devices that perform local processing of sensor data before transmission to the cloud. This segmentation reduces the bandwidth required for cloud communication by filtering and preprocessing data at the edge, thereby maintaining high data collection capacity while reducing bandwidth strain.
Solution Approach 2:
The patent implements selective data transmission where only relevant or anomalous sensor readings are transmitted to the cloud backend, rather than transmitting all raw sensor data. This partial action approach maintains comprehensive monitoring capability while significantly reducing the volume of data transmitted over the network.
3Reliability
If IoT devices are connected to computer networks for data transmission, then monitoring capability is improved, but security vulnerabilities increase making devices points of attack
Solution Approach 1:
The patent introduces multiple layers of intermediary devices including edge computing devices and gateway devices that act as security buffers between the IoT sensors and the corporate network. These intermediaries isolate the sensors from direct network access, thereby reducing security risks while maintaining monitoring capability.
Solution Approach 2:
The patent segments the network architecture into isolated zones with sensors in one zone, edge computing in another, and cloud backend in a third. This network segmentation limits the attack surface and prevents lateral movement of potential threats, thereby improving security posture while maintaining full monitoring functionality.
4Adaptability or versatility
If sophisticated integration of IoT devices with networking systems and platforms is implemented, then system functionality is improved, but deployment complexity increases requiring expertise that organizations may lack
Solution Approach 1:
The patent implements a universal gateway device that can interface with multiple sensor types and communication protocols through a single standardized interface. This universal gateway handles protocol translation and data normalization, thereby providing sophisticated integration capability while simplifying deployment for organizations regardless of their technical expertise.
Solution Approach 2:
The patent implements self-provisioning and automatic configuration capabilities where the mesh network and edge computing devices automatically discover and configure themselves upon deployment. This self-service approach reduces deployment complexity by eliminating the need for manual configuration and expert intervention, while still achieving sophisticated system integration.
Data Source
AI summary
A system can include a backend system and a sensor kit configured to monitor an industrial setting. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to the backend system via a public network. The backend system can include a processing system and a storage system, where the processing system performs backend operations on the sensor data and the storage systems stores the sensor data.