Autonomous space sterilization of air and floor with contamination index
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Solution Overview
Problem
Current systems lack an efficient and autonomous method for real-time air and floor sterilization in environments, failing to effectively adapt to varying contamination levels and communicate status among robotic devices.
Innovation Solution
A network-connected robotic device system that continuously monitors air purity and floor particle data, adjusts purification and cleaning modes based on thresholds, and transmits operating status to other devices, utilizing sensors, cameras, and UV-C disinfection systems for autonomous and coordinated sterilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional sterilization systems are used, then sterilization function is provided, but real-time adaptation to varying contamination levels is failed
Solution Approach 1:
The system continuously monitors air quality parameters (PM2.5, PM10, CO2, temperature, humidity) using sensors and uses this feedback to dynamically adjust UV-C lamp intensity and operation mode. The controller receives real-time data from air quality sensors and modifies sterilization output accordingly, creating a closed-loop control system that adapts to changing contamination levels while maintaining sterilization effectiveness.
Solution Approach 2:
The sterilization system transitions from static fixed-mode operation to dynamic adaptive operation. The UV-C lamps can operate in multiple modes (standby, low, medium, high intensity) and the system automatically transitions between these modes based on real-time air quality measurements, enabling continuous adaptation to varying contamination conditions.
2Adaptability or versatility
If autonomous monitoring and adjustment is implemented, then real-time adaptation is achieved, but device complexity increases
Solution Approach 1:
The robotic device integrates multiple functions into a single platform: air quality monitoring, floor cleaning, and air sterilization. The same device performs sensing, navigation, surface cleaning, and atmospheric purification, reducing the need for separate specialized devices and managing complexity through functional integration.
Solution Approach 2:
The system operates autonomously without requiring external control or intervention. The controller automatically processes sensor data, determines appropriate sterilization modes, and adjusts UV-C lamp operation independently. The robotic device navigates, monitors, and sterilizes environments self-managed, reducing operational complexity.
3Productivity
If fleet coordination is implemented, then coordinated sterilization is achieved, but communication infrastructure complexity increases
Solution Approach 1:
A cloud-based platform serves as an intermediary that coordinates communication between multiple robotic devices. Rather than requiring direct peer-to-peer communication infrastructure between robots, the cloud platform receives data from all devices, processes coordination logic, and distributes control commands, simplifying the communication architecture while enabling fleet-wide coordination.
4Reliability
If continuous monitoring is performed, then sterilization effectiveness is improved, but energy consumption increases
Solution Approach 1:
The system uses periodic sensing and intermittent sterilization rather than continuous operation. Air quality is monitored continuously at low energy cost, and UV-C sterilization is activated periodically or on-demand based on contamination thresholds. The system switches between standby and active sterilization modes, reducing overall energy consumption while maintaining effectiveness.
Solution Approach 2:
The UV-C lamp intensity parameter is dynamically changed based on air quality conditions. During low contamination periods, the system reduces lamp intensity to standby or low mode, conserving energy. When contamination exceeds thresholds, the system increases intensity to medium or high mode, ensuring sterilization effectiveness. This parameter modulation balances energy use with performance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time, adaptive air and floor sterilization, improving environmental cleanliness and safety by using sensor feedback to adjust modes and coordinate robotic actions, enhancing the effectiveness of sterilization processes.
Implementation Method 1
utilizing sensors, cameras, and UV-C disinfection systems for autonomous and coordinated sterilization
Data Source
AI summary
A method is disclosed that includes continuously obtaining air purity and floor particle data from one or more sensors and/or one or more cameras of a robotic device among a fleet of robotic devices; determining whether air impurities around the robotic device exceed an air purity threshold based on air purity feedback from the one or more sensors of the robotic device; based on the determination whether air impurities around the robotic device exceed the air purity threshold, modifying an air purification mode of the robotic device; determining whether floor particles around the robotic device exceed a floor particle threshold based on floor particle feedback from the one or more sensors of the robotic device; and based on the determination whether floor particles around the robotic device exceed the floor particle threshold, modifying a floor cleaning mode of the robotic device.