Clean Tech and Data Science Trends In The Age of Covid: Part I

 As Covid-19 sweeps around the world, we’re beginning to see the economic impacts from shutting down the economy in different countries. We’ve seen recessions and slowdowns before, most recently in 2008 and 2001, but this one feels different in several ways. First, the cause of the downturn is not a result of human antics, but a natural agent - a virus. Second, since we can’t really fix the economic issues unless the pandemic and infection rates are brought under control, the regular economic tools have limited impact. Third, this is probably the first time that the whole world is being impacted within a very short time, unlike the other downturns. This means that there’s no country or region that can act as a buffer or an economic engine for the rest of the world. Finally, it’s the sheer uncertainty in this situation - we’re still learning about the virus and there are a lot of open questions being researched now. For example, how it’s impacting different societies and populations, how it changes under different environmental conditions, what are possible treatment options, whether we’re going to see multiple waves of infections and so on. That means that we really don’t have a good sense of when this whole situation is going to come to an end and how we are going to be turning the economy back on. Epidemiologists, public health experts, economists are all working together on these questions, but they’re still very much up in the air.

So, what does that mean for various clean technology sectors?
At this point, we’re seeing an acceleration of the trends that were already changing different sectors in clean technology. Remote sensing, incorporating smart sensors into existing monitoring systems, robotics and autonomous systems for operations, building predictive models and better visualization tools using machine learning and data science - these are getting more important as the world shuts down and only essential operations are allowed.
Essential operations now definitely include energy and power production, farming and food production, water and wastewater treatment, waste management, city monitoring and management services. These are all clean technology sectors and normally each of them would have different issues and questions that need to be dealt with. However, right now a common theme is emerging among all of them - how can operations be conducted as safely and efficiently as possible - without endangering the people who work there? Public health guidelines require that only those who are absolutely essential are allowed to come to work in person and the rest be allowed to work from home.
The issue is that all these systems - energy, water, waste, farming, urban services - need constant monitoring and regular maintenance in order to function effectively. And we can’t just turn off a water treatment plant or a power plant, for example, without having huge negative impacts on people and public health.
How then can these systems be managed in times like this?
One option is to use smart sensors to monitor the operations of the power plants, treatment systems and other systems. This allows plant operators to evaluate the conditions of the system remotely and only send technicians in when a problem has been detected. That, in turn, means that fewer people are required to be physically present at the plant. These sensors are typically connected to the internet, monitor certain parameters in the system and generate that data at specific intervals. Many plants already have some form of sensors today, but it’s now becoming necessary to expand their existing sensor networks to either cover larger areas of the plant or to monitor additional parameters.
Another option is using robots to perform routine monitoring and maintenance tasks. Robots were already beginning to disrupt the farming sector, with companies like Blue River Technology using a combination of robotics, computer vision and plant science to identify weeds and harvest labor- intensive crops like lettuce. We’ve been seeing startups in the water and energy sectors that are building robots that can identify problems and do simple maintenance with remote guidance, but these are still at the initial stages. Startups and other groups working in these areas are likely to gain traction as companies start needing automated maintenance and monitoring.
We’re also seeing a lot of governments and companies using satellites, drones, autonomous vehicles and small unmanned aerial vehicles (UAVs) to get data, transmit information and packages, and provide aid and services. A lot of this was happening in agriculture, water and disaster management sectors already - but now we’re seeing increased incorporation of these technologies in cities. China, especially, has been aggressive in the use of these technologies in monitoring the status of the pandemic in the country, the health of their citizens and the presence of outbreaks in their cities in addition to delivering food, medicines and other essential items. The technology driving “Smart Cities” and urban sustainability is now going into overdrive as cities and governments all over the world figure out how to manage their cities and citizens’ needs. And it’s changing - earlier, the focus was on managing mobility, energy and improving access to green spaces. Now, the focus is on remote management of existing operations, delivery of essential services and public health. And as the lockdown eases and cities slowly start opening different industries, we could see interesting combinations of technologies and goals coming up.
The challenge in all this comes from using data science, including machine learning and AI, to answer the right questions and provide appropriate solutions. This is where having the combination of data science skills with knowledge of the clean tech sector is becoming very valuable to companies and organizations. Building teams with the right combination of skills, creating collaborations with existing companies and organizations, understanding what is really needed at this time and what is a “nice to have” are all essential aspects of getting ahead of the trends in data science and clean technology.
Next time, we’ll take a look at startups and the funding climate at this time. 

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