Markets Now Utilizing AMR to Improve Cleaning Efficiency

Current Application Scenarios

Cleaning Mission Plans

Path Learning Mode:  Not a copy cat…
  • At task starting point, TN70 scans the task code to start path learning
  • Promote robots where cleaning is required, establish cleaning paths, and view real-time route information through the screen
  • After the path learning is completed, save the task and complete the task setting. It is possible to adapt cleaning parameters, such as intensive or energy-saving mode .
  • High-precision path repeat function to meet high-demand repetitive cleaning tasks.
  • Constant and ongoing process improvement through machine learning algorithm
  • Improved efficiency and cleaning effectiveness over time

Product Technical Support – Cloud Platform – Remote Monitoring

Cleaning Statistics, Verification Reports, Remote Monitoring and Support

Sparkoz digital management cloud platform:
  • Self-developed Sparkoz robot information management platform
  • View the corresponding robot information by location , including:
  1. Current status, usage, software version, configuration information
  2. Overall working efficiency and utilization rate of the robot
  3. Task information, map information, consumables management, fault information
  4. View task report, robot real-time information
  5. Remote deployment is also possible
  • Realize the transparency of robot information, making supervision, operation and maintenance and other functions easier
  • Consumables management, provide regular maintenance reference, and guide customers to improve usage efficiency
  • When a fault occurs or a task is completed, a text message will be sent to notify the user, without affecting other work of the user
  • QTA software continuously improves work efficiency.

Reporting – Weekly, Monthly

Hospital Task Reports