Let’s look back on the most exciting new features and changes made in EIM, Locus’ environmental data management software, during 2019!
Cloud / SaaS
In this white paper, we focus on how EHS programs can benefit from integration and interoperability of a multi-tenant cloud platform and Internet of Things (IoT) platforms for managing, organizing, and monitoring the structured and unstructured data coming from various different sources.
Locus Technologies, the market leader in multi-tenant SaaS water quality, environmental compliance, and sustainability management, today announced that it is going all-in on Amazon Web Services, Inc., moving its entire infrastructure to the world’s leading cloud. By moving its flagship product EIM to AWS this month, Locus will complete its transition to AWS.
Multi-tenancy offers distinct benefits over traditional, single-tenant software hosting. A multi-tenant SaaS provider’s resources are focused on maintaining a single, current version of the application, rather than having its resources diluted in an attempt to support multiple software versions for its customers.
More recently, big data has become more closely tied to IoT-generated streaming datasets such as Continued Air Emission Measurements (CEMS), real-time remote control and monitoring of treatment systems, water quality monitoring instrumentation, wireless sensors, and other types of wearable mobile devices.
On 12 April 2019, Locus’ Founder and CEO, Neno Duplan, received the prestigious Carnegie Mellon 2019 CEE (Civil and Environmental Engineering) Distinguished Alumni Award for outstanding accomplishments at Locus Technologies. In light of this recognition, Locus decided to dig into our blog vault, share a series of visionary blogs crafted by our Founder in 2016.
In most industrialized cities around the world, drinking water is readily available and safe. Safeguarding groundwater (aquifers), streams, rivers, reservoirs, and lakes is crucial to continue delivering clean water on the tap. So is testing and validated water quality data.