Challenges A client in the agricultural sector needed to know whether satellite-retrieved soil moisture data was reliable.The satellite-based soil moisture data was needed to monitor droughts.The soil moisture estimation algorithm needed to be scalable. Xpertnest’s Solutions Retrieved soil moisture data.Took measurements using a Theta Probe instrument in India and COSMOS data in UK.Compared satellite-estimated data to data taken from the field. Value Delivered Found that software algorithms provided soil moisture data with 85-90% accuracy.Validated an algorithm to provide quality soil moisture data sets in any region of the world.
Challenges Xpertnest was asked to conduct hydrology studies to understand the flood risk and site drainage requirements at project sites.The client needed to be able to identify internal drainage areas and suitable locations to build rainwater harvesting structures. Value Delivered Estimated flood risks on project sites, considering rainfall for 10, 25, 50 and 100 years.Provided the extent of submergence and inundation on the project site during floods, with clear demarcations. Value Delivered Optimal design quality to reduce risks associated with project infrastructure.Improved flood prevention, reducing risk and lowering costs.
Challenges The agricultural sector in the Indian state of Karnataka required information to deliver timely and adequate irrigation.The information was needed at high granularity and at regular intervals, identifying water stress areas.IoT-based sensors only provide soil moisture data on a point scale while data supplied by drones was not economical. Xpertnest’s Solutions Xpertnest estimated soil moisture by combining multiple satellite data sources to improve granularity and provide data at regular intervals.Satellite-estimated soil moisture identified water stress areas at the desired scale, enabling stakeholders to make optimal decisions.The data enabled estimates of historical soil moisture data to predict likely crop yield. Value Delivered Reduced water...
Challenges A water utility wanted to identify undermanaged networks, understand behaviour in extreme conditions, and minimize water transmission losses.The utility was hoping to save money by reducing infrastructure.Any changes needed to stop the introduction of pathogens and contaminants from the surrounding network. Xpertnest’s Solutions Xpertnest developed a model to calibrate for field conditions the rate of water supply and pressure, the adequacy of infrastructure, and issues of quality.The analysis displayed areas of low and high leakage. Value Delivered The analysis detected dilapidated systems, saving water and energy.The utility was able to implement an efficient maintenance routine, substantially saving resources and finances.