Water Meter Reader AMR
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A Smart Water Meter
A Smart Water Meter is an essential solution to measure, monitor, control, optimize and carry out actionable tasks to reduce water waste and optimize activities directly resulting in controlled costs and a more sustainable usage habit. To enable and achieve this, ClodPi Labs (India) Pvt Ltd has come up with Automated Meter Reader (AMR) - a sustainable technology-driven solution for conserving water and practicing green concepts for residential and commercial buildings, guaranteed to make users more conscious of their water usage.
How does it work?
The solution devices once installed and configured, enables the system users to monitor water consumption patterns on the system's dashboard enabling the organization to set targets to achieve water efficiency and cost reductions.
Features
Identify potential illegal usage/waste/water leakage:
Water consumption data provides insights allowing better manage the resources: E.g. invisible water leakages, continuous water usage in common areas, huge consumption of water in commercial sites / industrial plantsfactories.
Bill generation:
Daily wise water consumption will help one to calculate your Water Bill at any point of time. This is more important for large factories such as a bottled water, garments or a beverage company.
Water consumption data for previous days:
Enables you to identify the specific day you consumed more water based on information received, further allowing you to manage / plan and the forecast demand and supply.
Online User Interface Application:
To facilitate login and monitor your water consumption. The app comes with above listed features whilst further allowing you to view your water consumption pattern.
User Benefits
Identify high usage (Daily / Weekly / Monthly)
Monitor the benefits of water saving initiatives.
Control Operation Costs
Fast and easy implementation.
Enable ideas for water saving initiatives
Cloud based managed service solution
Site wise water consumption data
Past Water consumption data and tend analysis