Partial Discharge (PD) activity is a precursor for insulation degradation which may eventually lead to catastrophic failure of the electrical equipment with severe social and economic consequences. It is therefore imperative that PD is detected and located at its early stages to permit repair or replacement prior to total failure. The IEC-60270 and IEC-62478 standards, respectively, define the conventional methods (such as current and voltage measurement sensing) and non-conventional methods (such as optical, chemical, acoustical, and electromagnetic (EM) measurement sensing) for PD activity monitoring in the electrical equipment. Ultra-high frequency (UHF) technique is a non-intrusive technique which is widely used for capturing EM emissions from PD, as EM waves are insensitive to pressure and temperature variations, propagates through all dielectric mediums and are suited for continuous real-time monitoring. In spite of the recent advances in this area of research, as well as the vast amount of literature already available, the adoption of this technique for large scale deployment in the field for PD activity measurements is yet to be seen. The reason for this inadequate deployment can be mainly attributed to the fact that realizing these systems is very sensitive to cost. In this talk, we propose to design and implement a simplified architecture for the detection and localization of PD events. The proposed architecture consists of a low profile circularly polarized ultra wideband antenna to capture the discharge events, a radio-frequency receiver signal chain to process the captured events and an Internet of Things (IoT) cloud to aggregate, visualize, and analyze the events in real-time. The performance of the proposed architecture as well as the localization algorithms will be evaluated using a full-scale test setup for different types of discharges.