Change in rainfall 2001-2016, global tropics

Map: Change in rainfall 2001-2016, global tropics

EnvironImagine

Real world quality control with environmental imagine.

Over the past decades spectroscopy has developed into a mainstream method for detecting substances, contents, pollutions and impurities etc. Spectroscopy is traditionally used within many science disciplines. The ongoing miniturization also means that spectrometers are now becoming handheld, reaching a broader consumer market. I believe that within a decade (the 2020s) smartphones will come with builtin spectrometers. Perhaps that will happen already in 2021 or 2022 even.

On the software side, the development of Machine Learning (ML) and Artificial Intelligence (AI) has paved the way for pattern recognition and improved estimations of sample, or image, content and compositions. But most spectrometers are used with proprietary software (apps). These apps have a steep learning curve and a large entry threshold. Few of them are Open Source. Hence, even if the hardware is developing, the software side does not follow, and there are no user friendly alternatives available for civic use. Developing such a software package could capture an enormous market for civic investigation of the state of the local to global environment. Simply, Giving (back) the power of understanding the environment and the quality of e.g.ingested air, food and drinks from the producer to the individual consumer

Based on ideas and algorithm developments that I have done over the past decades for interpreting mulit-spectral satellite images, I want to develop a new approach for interpreting spectral data, whether from multi-spectral (satellite) images or hyperspectral spectrometers. The method is graphical and users can add local or thematic knowledge. For instance, farmers and foresters with knolwedge on local soil and water conditions when monitoring soil fertility and mositure from satellite images, or vine-lovers analysing the content of vines from different years, districts or grapes. Due to pending patent applications I can not reveal anything about the central method yet.

Since I started this "project" in 2014, technology has matured. Not least because of the development of Internet of Things (IoT) and associated sensing and network technology. A new generation of sencors, microcontroller, communication and data transfer protocols, the growth of cloud computing and facilitated app development; all are important components for venturing into new opportunies for "Real world quality control with environmental imagine". People are requesting facts, not someone elses truth. The market potential for sensing your own environment, the products around, the stuff you eat and drink, is enormous. Smart farming, where IoT integrated sesning is now plowing new grounds (so to say) is estimated to have a market value of 23 billion USD in 2022.

The pages assembled here is just for me to keep track of the different aspects I need to juggle in order to expand my small corportation into a business offering an app (online tool or for download) that would allow civic users to become imagery citizen scientists.

Ventures with spectroscopy

Markets for spectroscopy sensing

Pitch and Business Model Canvas (BMC)

Funding opportunities

Initiatives to follow or link-in to?

Potential cooperation partners