Background and Objectives: Radio frequency identification (RFID) has paved the way for a plethora of monitoring applications in the field of oil and gas. Degradation in liquefied petroleum gas (LPG)/ liquefied natural gas (LNG) quality and pipe infrastructure can be a nuisance for the oil and gas industry in Qatar. Hence, a human centric cyber-physical-system (CPS) utilizing hybrid wireless technologies including RFIDs and other sensor motes can detect and prevent such hazards. CPS technique can be used for the oil and gas sector in Qatar with customized framework architecture, event detection and decision algorithms. The objective of this research is to allow maintainers and administrators to perceive and decide on top of the monitoring system to increase the performance and efficiency of the whole monitoring application. Methods: The sensors collect the data and send it to the base station through collaborating wireless technologies. At the base station the data is processed and algorithms were run to detect an event such as presence of moisture, abnormal pressure, temperature and defects in a pipe's infrastructure health. Human interaction will help to further refine the data for possible false alarms. Mobile applications can be used by the users/administrators to send details of a perceived event directly to the base station. Results: Experiments were performed on the moisture detection in Wireless Research Laboratory in Texas A&M University at Qatar. On the similar note, other sensors can also be associated with the RFIDs and their data can be relayed to the server. A framework architecture was proposed for the human centric approach of the detection and monitoring system. Conclusion: We propose a system where these RFID active tags with the sensors such as pressure, temperature, flow, strain etc., in collaboration with other wireless technologies, are able to send information regarding the gas quality and pipe's infrastructure health. The collaboration of RFIDs and other technologies helps us to create a smart human centric monitoring system. This will enhance maintenance and event detection such as the presence of moisture or strain on pipe's structure. It will additionally assist in the automatic adjustment of the valve's and pump's properties according to the detected events.