We are a group under the Victoria University of Wellington, New Zealand (NZ), building a distributed peer-to-peer transaction-based platform for the settlement of the social cost of farming based on “Sustainability Credit”. The marketplace facilitates stakeholders engagement by defining quantitative metrics, measurements, monitoring, and ensuring the issues of data governance, privacy, sensitivity to competition are solved. The platform provides for the measuring, reporting and certifying the products through the entire lifecycle from the origination to exporting, using available data from Geographic Information Systems (GIS), recording sustainable practices, production processes, mitigation of environmental damages, and pollution footprints.
The farming community in NZ is very much interested in objective, sensor data-driven information about their water and soil poallution impact and the connection to the export products, that are not simple model-driven estimates currently used by the government agencies. It is a great market opportunity to provide such a transparent, decentralised platform for farmers, government agencies, the insurance industry, and domestic users to both track and influence the link between the produce and pollution data. This may eventually make an impact on farming activities worldwide.
We are seeking Singapore-based public sector researcher performers with machine learning expertise required to conduct image analysis on GIS data, with the methodology of defining meaningful compound indices from hyperspectral/multispectral images available. This is to obtain data and correlate environmental impact with farming activities, via the use of historical and near real-time remote sensor data (satellite and drone imagery) and IoT modelling.
Environmental impact areas of focus include: