Water quality information dissemination at real-time in South Africa using language modelling

Domain:

natural language processingenvironment and energy

Record type:

paper

Creator:

LouPatHasSim

Publisher:

Host:

We present a conversational model to apprise users with limited access to computational resources about water quality and real-time accessibility for a given location. We used natural language understanding through neural embedding driven approaches. This was integrated with a chatbot interface to accept user queries and decide on action output based on entity recognition from such input query and online information from standard databases and governmental and non-governmental resources. We present results of attempts made for some South African use cases, and demonstrate utility for information search and dissemination at a local level. Accepted at the Machine Learning for the Developing World (ML4D) Workshop, NeurIPS 2018

Visit

doi.org arxiv.org

Licenses

arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Real-Time South African Sign Language Interpretation Using Computer Vision Methods

Water Quality Class Modeling Using Machine Learning Algorithms at Roodeplaat Dam, South Africa

Water pollution is a common problem for dams situated within an urban or agricultural catchment. Thi

IoT-enabled Real-time Water Quality Monitoring System for Sustainable Small-scale Aquaculture in Sub-Saharan Africa

Small-scale aquaculture in sub-Saharan Africa is significantly impacted by poor water quality, with

Harnessing Deep Learning for Real-Time Water Quality Assessment: A Sustainable Solution

International audience This study presents an innovative approach utilizing artificia

Hydraulic and Water Quality Modelling of Water Distribution Networks Using EPANET Software

In this study, hydraulic analysis of two water distribution networks was carried out using EPANET 2.