Cleaning Robot Dispatch Using Foot-Traffic Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large public places face challenges in maintaining cleanliness due to dynamic foot-traffic volumes and large cleaning areas, requiring continuous battery power from cleaning robots, which is inefficient and costly, as human inspectors must manually decide when to dispatch robots for cleaning tasks.
Innovation Solution
A system for dispatching cleaning robots that includes an input subsystem for monitoring foot traffic, a processing subsystem to determine cleaning tasks based on predefined parameters, and a communication subsystem to manage robot operations, allowing for intelligent decision-making and efficient allocation of cleaning resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cleaning robots are continuously deployed to maintain cleanliness in large public places, then cleanliness is maintained, but battery power is wasted and operational costs increase
Solution Approach 1:
The system employs foot-traffic monitoring devices that continuously collect data on pedestrian flow and transmit it to the control unit. The control unit processes this feedback information to dynamically determine when cleaning is necessary, replacing continuous operation with demand-driven operation. This feedback mechanism enables the system to respond to actual cleanliness needs rather than operating on a fixed schedule, thereby reducing unnecessary battery consumption while maintaining cleanliness standards.
Solution Approach 2:
The cleaning robot operates autonomously by receiving dispatch instructions based on processed foot-traffic data. The system self-regulates its operation schedule without continuous human intervention, automatically transitioning between idle and active states based on real-time environmental conditions. This self-service capability allows the robot to optimize its own energy usage by only operating when cleaning is actually required.
2Adaptability or versatility
If human inspectors manually monitor and dispatch cleaning robots, then cleaning decisions can be made, but labor costs and response time increase
Solution Approach 1:
The system replaces the mechanical process of manual inspection and decision-making with an automated electronic system. Foot-traffic monitoring devices continuously collect data, and the control unit automatically processes this information to generate dispatch decisions. This substitution eliminates the need for human inspectors to physically monitor areas and manually communicate cleaning needs, dramatically reducing response time while maintaining the flexibility to adapt to varying foot-traffic conditions through programmable algorithms.
Solution Approach 2:
The control unit serves as an intermediary between the foot-traffic monitoring devices and the cleaning robots. It receives raw data from sensors, processes the information according to predefined criteria, and translates it into actionable dispatch commands. This intermediary layer enables automated decision-making that is both rapid and flexible, eliminating the delays associated with human communication while preserving the adaptability to respond to different cleaning scenarios.
3Area of stationary object
If cleaning robots operate in large areas with dynamic foot traffic, then comprehensive cleaning coverage is achieved, but energy consumption and operational complexity increase
Solution Approach 1:
The system transitions from static, schedule-based operation to dynamic, condition-based operation. The control unit continuously receives real-time foot-traffic data and adjusts robot dispatch decisions accordingly. This dynamic approach allows the system to cover large areas efficiently by concentrating cleaning resources in high-traffic zones that require attention while reducing or eliminating operations in low-traffic areas, thereby optimizing energy consumption across the entire coverage area.
Solution Approach 2:
The system applies different cleaning strategies to different areas based on their specific foot-traffic characteristics. By analyzing localized foot-traffic patterns, the control unit can dispatch robots to specific high-need areas rather than uniformly covering entire large areas. This localized approach ensures comprehensive cleaning coverage where needed while minimizing energy expenditure in areas with lower cleaning requirements, effectively resolving the contradiction between coverage area and energy consumption.
Data Source
AI summary
The present application discloses a system for dispatching cleaning robots. The system includes an input subsystem configured to provide an input signal including information about foot traffic in a time period in an area. The system includes a processing subsystem to receive and process the input signal and further to determine a cleaning task under an operation scheme and generate a control signal for the cleaning task. Further the system includes a communication subsystem configured to receive the control signal from the processing subsystem and one or more first signals respectively from the one or more cleaning robots. The communication subsystem sends the control signal based on the one or more first signals to dispatch at least one cleaning robot to the area to perform the cleaning task and receives one second signal from the cleaning robot to update the operation scheme.