Control Tower - a new live map tooling

In a previous post, I already shared our Explorer tool, an in-house BI tool specialized for location data, which is inherited and enhanced from a popular tool called Kepler.gl to boost user productivity in 4 aspects: more convenient to load data directly from Metabase, more visualization with new map styles and map layers, more convenient to save and share map, and more insightful with data widgets. However, this tool also bears some trade-offs: unfriendly UX for non-technical users, too rely on other infrastructure such as Metabase and not ideal for operational monitoring with cleaner view.

Explorer is suitable for ad-hoc historical data analysis with BI/BA team, but not really shine with Operation/Managers. And that's why we built another tool named Control-Tower to meet our operational expectation in real-time scenario.

At glance, Control Tower is a map to see all supply and demand locations in a city with some beautiful visualization and numbers. We introduced some concepts learnt from similar products including layers (metrics),  widgets (a statistic view based on an data attribute) or coloring to quickly identify status of our objects. As you can see, the most interesting part of this tool is the beautiful front-end which is both simple and smart for users to immediately obtain information and trigger right actions at right time. Moreover, the challenge from behind the scene is that, we have to process a large amount of location data quickly and performant enough to justify the responsiveness at frontend and the stability of backend. To solve such problems, for the first time, we decided to implement this tool in many new approaches. Firstly, we chose frond-end-first development process: all data will be mocked at beginning to satisfy UI presentation, when we are happy with the UI/UX, we review and tweak the data format for better performance. Secondly, we divide our frontend into modules, where each is for a seperated use-case and specialized data format, so actually we don't have a fixed screen but we can deploy many different map views for different problems. Thirdly, we employed some cache/in-memory gis-specific databases to make sure the data is up-to-date and performant even with a lot of big queries at the same time.

Along with Explorer, Control Tower is a new generation of geospatial tool that AhaMove/OnWheel wants to build and solve real-life business problems relating to location data. Now, we are confident to have a full technology stack for geospatial problems, from infras services such as route/places/optimization till frontend tool like Explorer/Control Tower to find out feasible solutions as soon as possible. While our current product scope is quite small in comparison to other international colleagues in this ecosystem such as Locale.ai, Aspectum; we believe our expertise and locality knowledge should benefit more to local market, not only in logistics but other industries relating to land/location resources such as retail chains, agricultural/aqua farms, etc...

Imagine you have a lot of fish ponds/farms across Vietnam seasides, you would love to see a real-time map of your ponds with full of IOT statistics such as the salt/oxygen level, I believe this experience would be amazing and beneficial to your business

An advantage of OnWheel products like Control Tower  is that we are solving big scale problems at our brother AhaMove's on-demand delivery services; hence our use-case and solution are all well designed, detailed and technically scalable. Obviously, such problem are very specific and opinionated, but we are willing to tailor for you, if you find our approach makes sense to your use-case.