How Do Wastewater, Origami, Covid-19 and Remote Sensing Fit Together?
When you hear the words “remote sensing”, what do you think about? Drones taking pictures of streets? Spy satellites?
The chances are that if you’re in the clean technology field, you’re thinking about land use and land cover, mapping crop productivity, estimating water accessibility, monitoring air pollution - all very typical cases where data from satellites, drones, UAVs and cameras are used to observe environmental conditions and make predictions.
But, what about wastewater?
Now wastewater is typically the poor cousin of the water sector - we all need it, but we’d much rather not think about it at all! But it’s really important and as we’ve seen recently, can be used for more than just waste disposal.Right now, cities and countries around the world are monitoring wastewater to detect the spread of Covid-19.So far, sampling methods have focused on collecting traditional grab samples at the wastewater treatment plant or at other inlets in the sewer system. However, there’s increased interest in developing sensors that can monitor the system remotely at different points - though what that will finally look like is anyone’s guess right now.
Another option would be to think about a combination of remote observations and image detection. For example, in the case of these paper-based sensors, we could start thinking about the sensors being placed at strategic locations together with cameras that can capture the image on the sensor and an image detection algorithm that can identify whether or not the SARS-COV2 detection mark is there or not. Maybe, even robots equipped with these sensors could periodically traverse the sewer system so that images could be sent back?
While this is not a typical remote sensing problem, you can see how combinations of computer vision, sensors and remote operations can transform the wastewater industry, among others. And this transformation is likely to be sped up because of the pandemic and the need to develop novel methods quickly and effectively.
We're in the processes of building a couple of fantastic new offerings that many folks in our community have asked for - so blog posts will be limited for a few months. Our jobs portal will still be updated regularly to make sure that all our members can keep up with what's happening in the sector. We can't wait to share what's happening at our end!
The last couple of months have been interesting from a climate viewpoint - we’ve seen a record number of climate related disasters around the globe - drought, floods, fires, heat waves…..and it looks like this is probably going to be what our planet will look like in the near future. Add to that the COP26 conference that is scheduled for October 31st - and climate, sustainability and technology are front page news! So, let’s talk about one of the technologies in the news - artificial intelligence (AI) and its impact on climate, water, agriculture, energy, forestry, ecosystems and other sectors in clean technology . AI and its subset of tools - machine learning (ML), data science and statistics - are being touted as one of the key technologies in solving the problems facing the planet today. And while these technologies are certainly powerful - applying them effectively to solve problems in clean tech is another issue altogether. AI has been used by scientists in different clean tech se
Will AI transform water, energy, agriculture, climate and all the other clean tech sectors? Can AI transform these sectors? Some version of these questions always gets asked at any meeting or conference in clean technology. Of course, part of that is because there’s been so much hype around AI and the whole “software is eating the world” interviews that came out a couple of years ago. But part of it is also because these tools are so powerful that professionals working in these sectors can see the potential - but just aren’t sure if it’s applicable to their sector yet. So, let’s start by asking a couple of fundamental questions. Why do we need AI at all? Or any models for that matter? Models are used to understand the world - to estimate the impacts of changes in systems and to try and predict what will happen in the future. Typically, the approaches used in building models can be classified into three broad categories - physical or mechanistic approaches, statistical approaches and