In order to achieve the United Nations goal of carbon neutrality by 2050, it is necessary that fossil fuel production is reduced by at least 6% annually [1]. Road transportation is one of the most significant contributors to fossil fuel consumption but can be greatly mitigated if drivers are able to maximize their fuel efficiency. Our device addresses this by monitoring users' driving habits through the vehicle's OBD2 port and by providing live driving feedback for how to improve fuel efficiency. Aggressive driving is known to reduce gas mileage by up to 33% [2], so this solution shows great potential in addressing carbon neutrality monitoring within the road transportation sector. A recent study also showed that driver feedback devices can improve gas mileage by 10% for the average user and by 22% for users who are motivated to reduce fuel consumption [3].

Our device, the EcoBuddy, will connect to the OBD2 port of a user’s car and retrieve data such as speed, engine RPM, throttle position, and fuel consumption. The EcoBuddy then sends this data to the user’s phone. This data will then be used to analyze the user’s driving habits and their fuel efficiency. Feedback on how to improve their driving habits to increase fuel efficiency will be available in an app alongside graphically displayed vehicle statistics. Because the EcoBuddy can be used by any car with an OBD2 port, we can collect data on gas mileage for different car makes, models, and years. This information in combination with information gathered through APIs will be used in a rating algorithm which uses machine learning to give the user a driving score for each trip in terms of fuel efficiency and safety. This algorithm will additionally pinpoint areas of improvement for each user and give references explaining how changing the way they drive could save them money. This approach will motivate the user and, at scale, prevent tens of thousands of pounds of CO2 emissions.

Because the device is read-only, we will only need to protect the user’s history of distance traveled and fuel efficiency. To do this we will rely on existing solutions. All data will be stored in DynamoDB, and logins will be done using Firebase. All appropriate calls to the backend will require a respective JWT token. Access to the device will be carried out over Bluetooth for setup and Wifi after setup is complete. The Bluetooth connection will require a pin which is in an NFC chip on the device therefore Bluetooth connection requires physical access resulting in additional security.

Since every car produced after 1996 is legally required to have an OBD2 port, our product can be used by most cars on the road. Additionally, the EcoBuddy can easily be mass-produced. We can contract with an electronics manufacturer to produce our devices, and find a manufacturer to produce the housings for our electronics. We would then need labor to put the electronics in the housing. The user then only needs to buy one of these devices and download our app in order to use our product. Our predicted cost of production per device hovers around $12.41, which means we can make the EcoBuddy relatively affordable and accessible to vehicle owners.

Using a vehicle’s data to inform drivers of their carbon impact requires a completely new and innovative approach to OBD2 monitoring. Currently, there are two notable types of OBD2 devices that share vaguely similar functionality to the EcoBuddy: OBD2 emissions readers for state inspections and IoT fleet-monitoring systems. The data collected and interpreted during state emissions testing would be similar to that collected by our device for the purpose of analyzing carbon impact. However, this testing is conducted at most on an annual basis and does not provide the same continuous feedback as our device. Furthermore, emissions testing only looks into the state of the vehicle and is completely blind to the owner’s driving habits.

IoT fleet-monitoring systems provide constantly updating information such as speed, location, idling time, and other information across an interconnected network of vehicles, though this feedback is intended for larger-scale management. The data collected by these devices do little to inform driver’s of their carbon impact, if at all, and aren’t intended to be used by individual drivers. The EcoBuddy addresses the shortcomings of these systems and adds additional capabilities outside the scope of any existing product.

[1] “World's governments must wind down fossil fuel production by 6% per year to limit catastrophic warming,” UN Environment, 2020. [Online]. Available: [Accessed: 30-May-2022].
[2] D. L. Bleviss, “Transportation is critical to reducing greenhouse gas emissions in the United States,” WIREs Energy and Environment, vol. 10, no. 2, 2020.
[3] M. R. Jacobsen, “Fuel economy and safety: The influences of vehicle class and driver behavior,” American Economic Journal: Applied Economics, vol. 5, no. 3, pp. 1–26, 2013.
[4] Institute of Transportation Studies, University of California, Davis. ECODRIVE I-80: A Large Sample Fuel Economy Feedback Field Test (ITS-RR-13-15).


Our team is comprised of undergraduate engineers with backgrounds in electronic design, machine learning, and sensor systems. We share a passion for global decarbonization and believe creating a design for the IoT Innovation Challenge is a great opportunity to expand our awareness on topics surrounding carbon neutrality and foster our technical skills. Our goal is to produce results with the potential to leave a lasting impact in efforts to decarbonize our world. The particular issue we decided to address is carbon emissions associated with road transportation, one of the largest contributors to global emissions. 90% of the fuel used in transportation is petroleum-based [1], meaning poor fuel efficiency leads to a large amount of unnecessary emissions. Even in electric vehicles, poor power efficiency directly affects the amount of fuel needed to supply the power grid. This is why optimizing fuel efficiency is a necessity when it comes to decarbonizing. Once we understood the gravity of the issue, we became highly motivated to research a low-cost, innovative solution that demonstrates potential and tests our understanding of vehicle computers, sensor systems, IoT devices, and machine learning. We hope that the EcoBuddy will answer this call. [1] “Sources of Greenhouse Gas Emissions,” EPA, 14-Apr-2022. [Online]. Available: [Accessed: 30-May-2022].


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