The system employs a combination of advanced forward osmosis (FO) and low-pressure reverse osmosis (RO) technologies.

Initially, forward osmosis is used to draw water through a semi-permeable membrane using a natural concentration gradient, which requires significantly less energy.

This pre-concentration step reduces the load on downstream desalination processes.

Following this, the solution undergoes low-pressure RO to further separate the fresh water from concentrated brine.

The system implements machine learning algorithms to continuously optimize the membrane settings and energy usage based on varying conditions and composition of input brine, improving water recovery and operational efficiency.

The solution provides significant operational cost savings by reducing energy consumption compared to traditional methods, while increasing water recovery from rejects.

This makes the system both economically and environmentally superior, with potential to set new industry standards in sustainable water management.

The technical feasibility is high given the mature state of forward osmosis technology and recent advancements in membrane materials and AI optimizations.

The primary business barrier is initial investment cost, but operational savings and environmental benefits provide compelling incentives.

Competition is moderate with existing methods focused on traditional high-pressure RO.