Robot Cleaner Control Using Simplified IoT Device Coordination
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Solution Overview
Problem
Current standardization of machine-to-machine (M2M) and Internet of Things (IoT) technologies face challenges in achieving accuracy, flexibility, and cost-effectiveness due to issues like redundancy in communication data, high power consumption, and complexity in handling diverse sensor functions and future variations, leading to inefficiencies in data acquisition and processing.
Innovation Solution
A simplified communication protocol is introduced through a 'combination module' that includes both sensor and actuator functions, allowing for independent communication with a system controller using a cost-effective and easy-to-process method, and enabling data management and status control within units, which can be configured to perform specific functions and adapt to various devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a multi-leveled communication standard is used to accommodate various sensor functions and future variations, then adaptability and versatility are improved, but device complexity and communication data redundancy increase
Solution Approach 1:
The communication protocol is segmented into two distinct parts: a simplified base protocol for essential sensor data transmission, and an optional extension mechanism for additional functions. This segmentation allows the system to maintain simplicity while accommodating future variations through selective extension rather than requiring a complex multi-leveled structure from the outset.
Solution Approach 2:
The patent creates a universal base communication protocol that can handle core sensor data transmission across all device types. Future functional variations are accommodated through a standardized extension mechanism rather than requiring separate protocol layers, making the base protocol universally applicable while allowing for multi-functionality when needed.
2Measurement precision
If comprehensive data from multiple sensor-equipped devices is collected to improve estimation accuracy, then measurement precision is improved, but power consumption and communication data amount increase
Solution Approach 1:
The patent extracts only the essential and necessary sensor data for accurate estimation, transmitting minimal required information rather than comprehensive data sets. This extraction approach maintains measurement precision by focusing on critical data points while significantly reducing communication overhead and power consumption associated with transmitting and processing excessive data.
Solution Approach 2:
The system implements partial data collection by selecting and transmitting only the specific sensor data portions that are necessary for accurate estimation. Rather than collecting and transmitting all available sensor data (excessive action), the system performs partial action by filtering and sending only essential data, achieving the required precision with reduced energy expenditure.
3Adaptability or versatility
If standardization is updated frequently to accommodate new sensor functions, then adaptability is improved, but loss of time and implementation complexity increase
Solution Approach 1:
The patent establishes a preliminary and robust base communication protocol that is designed to be inherently adaptable to future sensor functions. By preparing this flexible foundation in advance with built-in extension capabilities, the system can accommodate new functions through incremental additions rather than requiring complete standard rewrites, significantly reducing the time and complexity of future updates.
4Adaptability or versatility
If XML format is used for communication data to achieve flexibility and extensibility, then adaptability is improved, but processing complexity and power consumption increase
Solution Approach 1:
The patent adopts a lightweight, simplified communication data format that is easier and less resource-intensive to process than XML. This simplified format achieves the necessary flexibility and extensibility through a more efficient structure that requires less computational power to parse and process, reducing both device complexity and power consumption while maintaining adaptability for various sensor functions.
Data Source
AI summary
A condition control of a robot cleaner is performed or service is provided with a user using the robot cleaner to improve the convenience of the user. Various data items obtained through a network connection are used in the condition control or service to estimate/determine a behavior, condition, or request of the user. Specifically, the operation of the robot cleaner is controlled based on operations of other associated devices disposed in the same room where the robot cleaner runs.