The essence to managing safety hazards and minimising damage is the accurate identification of the point of incidence and quick remedial action. ATHENA offers an OFC-based Linear Heat Detection system that can be installed in any flammable and complex environment. It comes with a detection accuracy of fewer than 5 metres, and a temperature accuracy of +/- 1 deg C. The average power consumption is a mere 25W.

The Real-Time Thermal Rating/Dynamic Cable Rating (RTTR/DCR) enables companies to operate power lines including transmission and distribution networks at maximum efficiency and higher voltages without compromising on the safety standards.

Traditional static rating-based systems, which are based on probabilistic methods, tend to assume the worst-case scenarios, and provide simple and conservative estimates of network capacity. As a result, the system is operated significantly below capacity or is overloaded leading to ageing and failure.

On the other hand, the RTTR/DCR systems use real-time data from real environmental conditions and loading to provide information on system capacity/thermal headroom and indicate which areas are stressed or underutilized. One of the key components of RTTR/DCR is Distributed Temperature Sensing (DTS) using the OFC cable. The temperature of the power cable can be measured continuously using DTS

Pipelines are the lifeline for millions of people, carrying natural resources to our homes and businesses. They transport oil and gas from the fields to refineries, storage facilities, or export terminals. But they can be vulnerable to pipeline intrusions that could lead to serious damage or accidents.

Pipeline operators need to continuously monitor their systems for anomalies in pressure and flow that could indicate a potential leak or rupture. To ensure safety and security, these abnormalities must be detected early enough so that action can be taken before any leaks occur. This is especially important when considering the environmental impacts of a large spill into groundwater aquifers or waterways, which would have devastating effects on local populations and ecosystems if not stopped quickly enough.

Pipeline Intrusion Detection System that uses machine learning algorithms has proven effective at detecting anomalies in data collected from various monitoring sensors along pipelines. ATHENA’s pipeline intrusion detection system can detect walking/running, manual digging, mechanical digging/ploughing and vehicles.

The controller can be placed in the pre-existing control room and uses the existing optical fiber cable (SCADA) along the length of the pipeline. The system can give a pre-warning in case of an intruder(s) access the pipeline with malafide intentions.