Demo explanation of how we utilized Elasticsearch to build a robust data pipeline for IoT based Predictive Maintenance. We want to showcase how we used below Elastic functionalities to monitor IoT data of machine parameters and predicted its remaining useful life using machine learning models.
@PriyanshNegi and @Ashsenior serve as Founding Engineers at PredCo AI, leading the development of building an efficient data pipeline to collect IoT data from machine parameters and predicting its remaining useful life. They have a solid year of experience learning about Elastic products and how useful it is in the IoT domain. Having successfully built a SaaS startup previously, they are currently pursuing AI & ML Engineering, aspiring to solve challenging problems by coupling existing solutions and innovating strategies to overcome hurdles.
Description
Demo explanation of how we utilized Elasticsearch to build a robust data pipeline for IoT based Predictive Maintenance. We want to showcase how we used below Elastic functionalities to monitor IoT data of machine parameters and predicted its remaining useful life using machine learning models.
(Features involve : Anomaly detection, machine learning, grok patterns, file visualizer, index patterns, kibana, file beats, machine beats, logstash, rules, api, watchers etc)
Speaker Bio
@PriyanshNegi and @Ashsenior serve as Founding Engineers at PredCo AI, leading the development of building an efficient data pipeline to collect IoT data from machine parameters and predicting its remaining useful life. They have a solid year of experience learning about Elastic products and how useful it is in the IoT domain. Having successfully built a SaaS startup previously, they are currently pursuing AI & ML Engineering, aspiring to solve challenging problems by coupling existing solutions and innovating strategies to overcome hurdles.