IoT Sensor Packet Precomputation for CPU-Free LPWAN Nodes
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Solution Overview
Problem
Low-power wide-area network (LPWAN) end nodes require efficient data transmission mechanisms that do not rely on real-time processing, as they often operate in resource-constrained environments without CPUs, necessitating pre-computed data for message packets and waveform configurations to simplify operations and reduce complexity.
Innovation Solution
The implementation of a reduced-complexity end node system that stores pre-computed sensor event messages and waveform data, allowing for the selection and transmission of pre-defined message packets and RF signals without real-time processing, using control circuitry to determine the appropriate message and waveform based on detected events, and omitting the need for a CPU.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time processing is implemented in end nodes, then data transmission accuracy is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent applies preliminary action by pre-computing message packets and waveform configurations before deployment. The end node stores these pre-computed data in memory, allowing it to transmit data without performing complex real-time processing operations, thus maintaining accuracy while reducing device complexity
Solution Approach 2:
The patent extracts the complex processing operations from the end node and relocates them to a configuration stage or external system. The end node itself is simplified to only perform basic functions like storing pre-computed data and transmitting it, separating the heavy computational tasks from the resource-constrained device
2Productivity
If CPU is included in end node, then real-time data processing capability is improved, but power consumption and device complexity increase
Solution Approach 1:
The patent removes the CPU from the end node architecture entirely, extracting the processing capability from the device. Instead of having a CPU perform real-time computations, the system uses pre-computed message packets stored in memory, eliminating the need for power-consuming processing operations at the end node
Solution Approach 2:
The patent applies preliminary action by performing all data processing operations before the end node is deployed. Message packets and waveform configurations are prepared in advance and stored in memory, allowing the end node to operate without a CPU and consume minimal power during transmission
3Device complexity
If pre-computed data is stored in memory, then real-time processing requirements are reduced, but memory size and device complexity increase
Solution Approach 1:
The patent applies parameter changes by optimizing the structure and size of stored message packets. The pre-computed data is organized in an efficient format that minimizes memory requirements while providing all necessary information for accurate data transmission, balancing memory size against processing complexity reduction
Data Source
AI summary
A reduced-complexity Internet of Things sensor is disclosed. An example apparatus comprises memory storing one or more sensor event messages, a radio configured to determine a sensor event, a counter configured to output incremental counter states, and a control circuitry. The control circuitry may be in communication with the memory, the radio, and counter, and the sensor. The control circuitry may be configured to determine, based on the sensor event, a select sensor event message of the one or more sensor event messages. The control circuitry may be further configured to output, via the radio signal, a packet comprising the select event message and an indication of a counter state associated with the sensor event message.