Abstract: In this study, an intelligent and ingenious way of tracing the bearings of decomposed, crumbled and burnt food with the help of rule-based reasoning and Apothegm topiary has been presented. The data being acquired from various sensors in a kitchen environment is captured, interpreted and analysed based on the widely leveraged time-series phenomenon. The interpretation procedure is strictly rule-based that includes finding references of the odour in the kitchen from various roots that includes decayed food in the refrigerator, rotten things from the trash bin, some left outs in the wash basin and over cooked or burnt food in the oven. The inspiration for this research work came from the distinguished context-aware capability of Smart Sensor Networks (SSNs). That is, in any environment today, smart sensors have the inherent capability of connecting with one another wirelessly in their vicinity and with remote ones via., networking. The data originating from different sensors get fused appropriately to bring forth pragmatic and easily utilizable context-sensitive information accordingly to empower humans in time. Here in this case, sensors are collaboratively figuring out the decayed and crumbled food particles that cause many diseases which we are not aware of. The frame of reference is tried and tested in a smart kitchen which is embedded with well suited and well-timed sensors that stakes the scoop of context-aware environment. Furthermore, this implementation collars the real time infrastructure tracking that includes laboratories, chemical factories and security concerning spheres.