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The current method of outdoor CO2 monitoring is difficult and challenging as it is highly sensitive to an environment that is constantly changing, easily affecting the data of a single sensor for example when a car passes by, temporarily spiking readings. The method used to overcome this issue is to make use of a grid of sensors over an area of interest. This will allow outliers in the readings to easily be identified and accounted for, providing an accurate CO2 readout of the target area. However, this greatly increases the cost and complexity of monitoring putting it out of reach of smaller organizations.

Our idea to solve this issue is to employ the use of an autonomous drone which can carry a CO2 sensor along a preplanned route. The drone will be able to create a virtual “grid” of sensors to overcome the initial issue stated above but at a much lower cost. This will enable smaller associations such as businesses to start effectively monitor their environmental carbon output, instead of restricting it to parties with large funding such as governmental bodies.

This method of monitoring greatly improves on a couple aspects. First is cost, instead of requiring 100s of sensors, the drone will be able to fly a preplanned route continuously to gather a datamap over time. For example the parking lot outside a business. Secondly is the ease of use, as the drone will be able to operate autonomously, minimum effort will be required by the operator to keep the drone on route or to gather data. This makes it possible for a single technician with minimal technical knowledge or training to operate the drone, adding onto the accessibility of this project. Making carbon monitoring accessible is what will improve the effectiveness of carbon neutrality efforts as they obtain more reliable data to work with.

As mentioned above, this project makes it much more attainable and accessible for smaller scale businesses and entities to perform effective environmental carbon monitoring. This opens the opportunity for said businesses to be able to identify the effectiveness of different carbon neutrality protocols that they might have in place. As the proposed system does not require on site setup, it can easily be transported to any location where the user requires. This is beneficial to parties with larger areas of interest, say a university campus. As for what makes the data obtained effective in addition to being accessible, is that again, for what is comparably a smaller budget, the user will still be able to obtain a large data map with one sensor allowing for more accurate data and a larger sample size of data. This makes identifying the effectiveness of carbon neutrality efforts easier and more accurate, and also prevents the wasting of resources waiting on data to determine whether a new implementation is effective or not.

As the drone will be autonomous, its coverage is virtually limited only by its flight time, however practically, return time and data connection range will have to be considered as well. Referencing available technology on the market, it is not unreasonable to equip the drone with antennas that can transmit the readings as far as 2km away and with an estimated minimum flight time of 30 mins for the proposed fixed wing VTOL hybrid design, the flight range will far exceed the connection range. The design idea is again better than methods deployed in the status quo as, as long as the target monitoring area is within the drones flight range, the operator can easily configure exactly how long or how wide of a data map they wish to obtain by changing certain variables within the control software.

The drone will be equipped with an Arduino microprocessor on board, which will be able to monitor its heading and balance with the help of vision sensors, accelerometers, gyroscopes and gps positioning which then instructs the ardu flight controller to adjust thrust and control surfaces to keep the drone along the preplanned flight route. This essentially makes the drone autonomous once the directives have been configured preflight by the operator.

As everything is processed on board, and the data gathered can be stored locally, therefore should the connection to the operator be interrupted, no data will be lost. Apart from a gps signal, the drone will be able to operate without connectivity. In the case that the gps signal be lost or interrupted, the remaining sensors will still be able to assist the drone to land itself. During normal operation the drone will be connected to the operator’s receiver to receive location and live readings.

To prevent the data transmitted from being unintentionally accessed, the signal will be encrypted. Apart from that, the software that is run on the drone will be password protected to ensure that should the drone perform an emergency landing and be obtained by a third party, they would not have access to the drone’s functions. Therefore only the operator with the password will be able to log in and make changes to the parameters/access the monitored data.


Our team was working on a project to build an autonomous drone but when we saw the Keysight challenge, we asked ourselves if its possible to apply that for this purpose. After quite some research, we were sure that we could put our own project to good use by aiding in the global efforts of going carbon neutral and started to come up with ideas and ways to re-engineer the drone which resulted in the entry we have submitted.


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