Flexible Mesh Network for Clinical Asset Tracking
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Solution Overview
Problem
Current Real Time Locating Systems (RTLS) in healthcare environments face challenges in accuracy and adaptability, struggling to effectively track assets and personnel due to varying clinical settings and the need for flexible, robust networks that can handle diverse orientations and changing needs.
Innovation Solution
A flexible mesh network architecture that enables peer-to-peer connections between nodes, allowing for customizable network size and topology, and the ability to identify and re-subscribe to alternative services in case of interruptions, while also facilitating communication through firewalls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a traditional RTLS architecture is used in healthcare environments, then the system can provide basic location tracking, but the accuracy and adaptability are insufficient for diverse clinical settings
Solution Approach 1:
The system segments the RTLS into multiple independent nodes (fixed nodes, mobile nodes, tags) that can be selectively deployed and configured. Each node operates semi-autonomously, allowing the system to be adapted to different clinical environments by adding or removing specific node types without redesigning the entire system.
Solution Approach 2:
The mesh network topology is dynamic and self-organizing, allowing nodes to join and leave the network as clinical needs change. The system automatically reconfigures routing paths and service subscriptions when nodes are added or removed, enabling adaptability to evolving clinical settings while maintaining location tracking accuracy.
2Adaptability or versatility
If a rigid network topology is used, then the system structure is simple, but the system cannot handle diverse orientations and changing needs of clinical environments
Solution Approach 1:
Each node in the mesh network is designed with universal functionality, capable of acting as both a client and a service provider. Nodes can host multiple services (location tracking, routing, data aggregation) and simultaneously consume services from other nodes, allowing the same hardware to adapt to different clinical orientations and needs without requiring specialized configurations.
Solution Approach 2:
The mesh network implements self-service through automatic service discovery, subscription management, and routing path determination. When new nodes are added to the network, they automatically discover available services, subscribe to relevant ones, and integrate into the existing topology without manual configuration, reducing the perceived complexity while maintaining high adaptability.
3Reliability
If unidirectional client-service mode is used, then the network control is simple, but the system lacks robustness against network interruptions
Solution Approach 1:
Nodes perform preliminary actions by maintaining service lists and subscription information locally before network interruptions occur. When a node joins the network, it proactively discovers and subscribes to relevant services in advance, storing routing information and service metadata. This preliminary preparation ensures that services continue to function during network interruptions, as nodes can operate with cached information and automatically re-sync when connectivity is restored.
Solution Approach 2:
The mesh network uses intermediate nodes as mediators to maintain communication during interruptions. When direct connections between nodes are disrupted, data can be routed through intermediate nodes that relay information between disconnected parts of the network. This intermediary mechanism provides robustness against interruptions while distributing the connection management complexity across multiple nodes rather than requiring centralized control.
4Adaptability or versatility
If centralized service management is used, then the system is easy to manage, but the system cannot easily subscribe to alternative services when interruptions occur
Solution Approach 1:
The system implements feedback mechanisms where nodes continuously monitor service availability and network conditions. When a service becomes unavailable or a node leaves the network, receiving nodes detect this change and automatically generate feedback requests to subscribe to alternative services. The service lists are dynamically updated based on this feedback, allowing the system to adapt to changing conditions while maintaining relatively simple operation through automated service management.
Solution Approach 2:
Service lists act as intermediaries between nodes and services, providing a decoupled mechanism for service management. Instead of direct node-to-node service management, nodes interact with services through the standardized service list interface. This intermediary layer simplifies operation by providing a uniform method for discovering, subscribing to, and managing services, while simultaneously enabling flexibility to switch between alternative services when needed.
Data Source
AI summary
An example system connects to a location engine in a mesh network, transmits a first message indicating a bus master service hosted by a bus master, and receives a message indicating a location service hosted by a location engine and an aggregation service hosted by an aggregator connected to the location engine. The bus master stores a first entry corresponding to the location service and a second entry corresponding to the aggregation service. The bus master transmits a request to access the location service; receives a response confirming a subscription to the location service; and receives timing data indicating times at which the multiple receivers in a clinical environment received a wireless signal from a tag. The bus master aggregates the timing data into a data stream and transmits data stream to the location service in accordance with the subscription.