You will be able to use this item to analyse water sample and determine their degree of purity. Follow this tutorial and you ll also learn how to take readings with your water probe and how the probe works.In the last section, you ll learn how to plot the values recorded by your water probe on a shared online map, and launch a citizen science project on zooniverse.com to communicate about your findings as well as to engage other people in your research.
It is a medium sized clock that acts as a focal point in any room. People will immediately see it, and say “Wow!”. We can make the face using a range of colors and face treatments to match your style.
There are a range of available mounting options, ranging from sitting the clock on a shelf, through mounting the clock on a wall. Using a recessed power point will ensure that the clock can be wall mounted without the power cord showing.
par un capteur de pression, température et humidité BME280. Les valeurs sont affichées sur un écran Grove LCD I2C RGB Backlight v4.0. Une LED ring est allumée en différentes couleurs en fonction de la valeur de température. La luminosité de la LED est contrôlée par un potentiomètre.Les valeurs de la température, l'humidité et la pression atmosphérique sont affichées sur le Serial monitor
A group of young innovators from six hubs across (Media Organizations) East African Countries of South Sudan, Uganda and Kenya came together for ASKnet Training in Adjumani district of Uganda for 14 days in October, 2019. The training was conducted by r0g Agency for open culture and critical transformation through the financial support from German Federal Ministry for Economic Cooperation and Development.
During the practical part of the training, this group came up with an idea of building a bottle water fan from scratch. Before we started, the team list the materials and tools needed to complete the project, and where collected in one place.Take your time to pass through all the processes as documented below
[WORK IN PROGRESS]This smart thermostat is an electronic, programmable, and self-learning Wi-Fi-enabled thermostat that optimizes heating and cooling of homes and businesses to conserve energy. It is based on a machine learning algorithm: for the first weeks users have to regulate the thermostat in order to provide the reference data set. The thermostat can then learn people's schedule, at which temperature they are used to and when. Using built-in sensors and phones' locations it can shift into energy saving mode when it realizes nobody is at home.