Inlet Labs Blog

Data science and machine learning present new opportunities for improving public spaces. Leveraging these technologies for smart cities can make our communities more livable, more sustainable, and benefit local economies. They can assist with understanding key questions in city planning and urban design such as how public spaces are used, how many users there are, and who the users are. In this post, we'll look at a proof-of-concept system we implemented to answer these questions using machine learning for video analysis. Read on...


Water is a critical resource in the Pacific Northwest. The effects of climate change on hydrological resources will be felt by a wide range of communities. Cities, First Nations, farmers, and the environment will all be affected. Effective management of water resources will become increasingly important to meet the diverse needs of the region. Read on...


Visualizations are a great tool for gaining intuition about a dataset. When the dataset has a geo-spatial component, overlaying the data on a map can be a starting point for exploratory analysis. In this blog post I want to share a map of industrial facility greenhouse gas emissions in British Columbia. It's based on this 2016 dataset, wich covers industrial facilities emitting 10,000 tonnes or more of carbon dioxide (C02) equivalent per year, as well electricity import operations in British Columbia. Read on...


Neural networks generate a lot of interest. However, it’s not always clear to people outside of the machine learning community the problems they’re suited for, what they are, or how they’re built. We’ll address these topics in this blog post, aiming to make neural networks accessible to all readers. For those with programing experience, I’ve appended a Jupyter Notebook at the end which you can follow to build your own neural network. Read on...