A platform was designed to allow electrical measurements to be taken from graphene sensors without the need for a probing bench or other lab equipment.Research began with the characterization of a range of different sensors, including various types of graphene field-effect transistors (GFET), interdigitated electrodes (IDE), and Hall sensors. Out of all the dropcast FETs that were tested, 23.6% were within a 20% margin of the expected resistance. Testing for Hall sensors involved measuring resistivity and hall coefficient on a set of two bars that were perpendicular to the direction of the current. 9 out of the 64 hall sensors tested had resistivity and hall coefficients that were within 10% of each other on each bar. A selection of sensors, namely the hall, dropcast GFET (or "droplet"), and infrared sensors then had circuit boards designed to house them. The PCBs were designed to be connected to the GPIO of a Raspberry Pi, which could then supply voltage and read measurements using a MATLAB script. The hall and droplet sensors had two variants designed for them, one with fewer components to be used in conjunction with an ADC expansion board for the Raspberry Pi, and a more complex board with an on-board ADC. ADC variants for the boards were simulated in LTspice, while testing of the platform was done with a Graphenea S20 GFET chip mounted on one of the IR boards and included a breadboard and resistor to create a voltage divider. After initial calibration, resistance measurements from the Raspberry pi were accurate within 1% to those taken with a semiconductor parameter analyzer.iii A method was developed to successfully refresh the graphene with acetone without damaging the PCB, raising the resistance of the GFETs by 701Ω on average.Results from using wax encapsulation to slow or stop resistance drift are inconclusive, the chip with wax had average resistance that shifted −40.1Ω to +25.5Ω per day, while the resistance drift on the chip without wax was −75.4Ω to +52.2Ω per day.There are several people who I would like to thank for the assistance that they have provided me while completing this work, whether in the form of inspiration, knowledge, finances, or labor.First and foremost I would like to thank my supervisor, Rony Amaya, for the guidance and support that I have received throughout this research.I would like to thank Brian Kennedy for supplying the graphene sensors used in this project, as well as funding for the research. Wenyu Zhou for designing most of the sensors used in this research and providing the information needed to test them and integrate them with the larger system. As well as Daniel Christakos for assistance in verifying the hardware and software.Waqar Ahmad and Otto Benedeczky for helping me learn how to use Altium Designer and giving tips on reducing board costs. Nagui Mikhail for getting me set up in the lab at Carleton, and supplying me with the equipment I needed for sensor characterization. Robert Vandusen for helping to develop and perform the acetone wash and wax encapsulation/remo...