Autonomous Asset-Tracking Node for Low-Connectivity Routing
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Solution Overview
Problem
Existing wireless sensor network protocols face challenges in scalability and demand excessive radio activity, making them unsuitable for dense low-power networks used in asset tracking, especially in environments with limited or no network connectivity.
Innovation Solution
A system that enables sensor nodes to make routing decisions and handle exceptions using a chain of transfers between gateways, employing Near Field Communication (NFC), Wi-Fi, and other wireless technologies, allowing for communication even when connectivity is limited or absent, and utilizing a microcontroller unit (MCU) with RF modules and a battery for power, along with persistent storage for data and cryptographic security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If existing wireless sensor network protocols are used, then network coverage can be established, but radio activity becomes excessive and scalability is restricted
Solution Approach 1:
Nodes perform self-routing decisions based on local information about the network topology and asset destination, eliminating the need for continuous centralized control and reducing overall network radio activity. Each node independently determines the next hop for packets, enabling the network to scale without proportionally increasing control overhead.
Solution Approach 2:
Nodes pre-calculate routing paths using destination-based routing tables that are updated periodically or event-driven. This preliminary routing decision-making reduces the need for real-time routing queries and broadcasts, thereby reducing radio activity while maintaining network coverage.
2Area of stationary object
If existing wireless sensor network protocols are used, then network coverage can be established, but scalability is restricted
Solution Approach 1:
The network is segmented into autonomous nodes that each maintain independent routing tables and make local routing decisions. This segmentation allows the network to scale by simply adding more nodes without requiring reconfiguration of the entire network, as each node independently adapts to network changes through localized routing table updates.
Solution Approach 2:
Routing tables are dynamically updated based on changing network conditions and topology. Nodes can adapt their routing decisions in real-time based on received routing information from neighboring nodes, enabling the network to scale flexibly as nodes are added or removed without disrupting overall network coverage.
3Loss of information
If cloud connection is required for asset tracking, then comprehensive information can be gathered, but operation fails when network connectivity is absent
Solution Approach 1:
Intermediate nodes in the wireless sensor network act as mediators that can store and forward asset tracking information. When cloud connectivity is unavailable, these intermediate nodes maintain the tracking functionality by relaying information between assets and any available gateway, ensuring operation continuity while preserving information completeness.
Solution Approach 2:
Routing tables and network topology information are pre-loaded into nodes before connectivity is needed. This preliminary action enables nodes to immediately begin routing and tracking operations when deployed, and maintains functionality during connectivity outages by using cached routing information until updated connectivity is restored.
4Measurement precision
If centralized routing control is used, then routing decisions can be optimized, but response time increases when assets are out of gateway range
Solution Approach 1:
Nodes perform self-routing decisions based on local routing tables that contain destination-based routing information. This eliminates the need for assets to maintain continuous communication with central gateways for routing decisions, enabling immediate local routing adjustments even when assets are out of gateway range, thus reducing exception detection time while maintaining routing optimization through pre-calculated paths.
Data Source
AI summary
Lost, misplaced, incorrectly delivered, and damaged assets are a common occurrence in shipment or asset tracking. Disclosed are various embodiments concerning a battery-less or intermittent battery use environments in which a node uses internal logic (e.g., circuitry and/or software) that, based at least in part on sensor information and stored information regarding the history of the node, may track events that have occurred to the node. The node may be responsive to events and determine whether exceptions have occurred that require attention. For example, detecting damage might cause the node to update an output to indicate the node and associated material, if any, needs to be rerouted to address the exception.


