Smart cities aren’t quite a reality yet, but we’re getting closer than ever. In a VentureBeat article, iMerit’s Chief Revenue Officer, Jeff Mills explains how to obtain the right geospatial data that is critical for powering autonomous technology and smart city projects.
Here are 3 key takeaways from the article:
- By collecting real-time inputs from various sensors, dynamic geospatial data can be used to power autonomous tech and smart city projects. We’ll be able to know and predict when there’s a spike in pedestrian traffic, the best cadence for trash collection, the ebbs and flows of automotive congestion, the impact of specific or random events on city operations and much more.
- The robust annotation of data is a key piece to ensuring our autonomous technologies and systems work like they’re supposed to. Properly addressing edge cases and anomalous scenarios helps the technology make the correct decisions and function properly, even in new or uncommon situations.
- We can’t possibly know every single edge case or anomalous situation the technology will run into, which is why it’s also important to share data. If companies share their data both with each other and with their local governments, it could allow our cities to reach a whole new level of smart — becoming more efficient and more effective.
Therefore, data collection from multiple sensors, robust annotation of the data, and data sharing are three ways for obtaining the right geospatial data to build smart cities.
Read the complete article here: Building smart cities starts with the right geospatial data