The current method of operating the Thannermukkom Barrage, spanning 1.427 km across the Vembanad Lake, is reliant on manual decisions made through consensus meetings involving stakeholders such as district collectors, fishermen, farmers, and officials. This process is time-consuming and inefficient, taking two to three days to regulate the 90 shutters across three stages, which are operated mechanically and electronically.
The regulation of these shutters is critical to managing salinity levels and water flow to prevent salinity intrusion, protect paddy crops from ecological degradation, and ensure fish availability. However, the current system is unable to respond dynamically to changes in salinity and water levels.
To address this, there is a need for an AI-based mechanism capable of:
Automatically detecting salinity levels and water flow.
Operating the shutters autonomously based on predefined conditions
Closing shutters when salinity reaches 1.8 ppt.
Opening shutters when water levels in the southern side exceed those in the northern side, with flow directed towards the sea and salinity below 1.5 ppt.
This automation would significantly reduce the time required for shutter operations to just 30 minutes, compared to the current duration of two to three days, resulting in better management of salinity intrusion, enhanced ecological balance, and improved efficiency in agricultural and fishing activities.
