This paper presents prototype implementation of low-cost, open hardware, static — gesture recognition system. The implemented system has three major components: A Glove and Sensor Unit (GSU) — consisting of a pair of gloves embedded with custom made, low-cost flex and contact sensors, a Primary Supporting Hardware (PSH) that maps change in input values from GSU, a Secondary Supporting Hardware (SSH) that processes the input values and recognizes the gesture accurately. When a gesture is signed, the GSU tracks the change in orientation of the fingers, which results in a change in voltage levels of the sensors. This change is mapped by the PSH and passed on to SSH which comprises of two ATmega328P microcontrollers, one connected to each of the glove. The two microcontrollers are connected in a master-slave configuration and communication between them is facilitated through an XBee module. The performance of this gesture recognition system is evaluated using a data set comprising of 36 unique gestures. These gestures represent a total of 120 gestures that include all gestures across five globally used sign languages. A gesture recognition engine that resides in the master microcontroller processes the input and identifies the gesture. The gesture recognition engine comprises of a two stage selection-elimination embedded intelligence algorithm that is used to enhance the system efficiency from 83.1% to 94.5% without any additional hardware. The cost of the system is USD 30, which the authors believe on commercialization, could be brought under USD 9.