# An Autonomous Thermal Camera System for Monitoring Fumarole Activity
###### Abstract  
The Kenyan part of the East African Rift System hosts several geothermal fields for energy production. Changes in the extraction rate of geothermal fluids and the amount of water re-injected into the system affect reservoir pressure and production capacity over time. Understanding the balance of production, natural processes and the response of the geothermal system requires long-term monitoring. The presence of a geothermal system at depth is often accompanied by surface manifestations, such as hot water springs and fumaroles, which have the potential for monitoring subsurface activity. Two thermal camera timelapse systems were developed and installed as part of a multi-sensor observatory in Kenya to capture fumarole activity over time. These cameras are an aggregation of a camera unit, a control unit, and a battery charged by a solar panel, and they monitor fumarole activity on an hourly basis, with a deep sleep of the system in between recordings. The article describes the choice of hardware and software, presents the data that the cameras acquire, and discusses the system's performance and possible improvement points.  
autonomous; camera; thermal infrared; time-series; fumarole; geothermal; Olkaria 2024249  
generation, the overall mass of extraction exceeds what is re-injected; in the long term, balancing is needed to maintain reservoir pressure and production capability. Finding this balance requires long-term monitoring of production, natural processes, and the response of the geothermal system.  
A geothermal system often has surface manifestations such as hot water springs, steaming grounds, fumaroles, and hot grounds [1]. In Olkaria, numerous volcanic craters, old lava flows, hot grounds, and fumaroles can be found. The fumaroles exhibit temperatures of over 363 K (90 \({}^{\circ}\)C). The geothermal activity and associated heat fluxes measured at the surface can vary over thousands of years [7], decades [8], and even seasonally [9]. To capture some of these natural fluctuations in fumarole activity, as well as those related to the operation of the reservoir for electricity production, long-term monitoring solutions are required to operate autonomously for extended periods with low maintenance pressure. Since the optimal observation time-of-day for monitoring these fumaroles was not known, time-series recordings with an observational frequency of once per hour were chosen as the trade-off between data availability, data volume, and power consumption.  
This article describes two thermal-infrared time-lapse cameras that monitor fumaroles in Olkaria to capture, as part of a multi-sensor field observatory, the geothermal system's dynamics. In particular, the article describes the choice of hardware, the control soft  
Figure 1: (**a**) The East African Rift System (EARS) with continental surface expressions indicated in red. The Kenya Rift System is the part of the EARS that crosses Kenya. (**b**) Volcanoes and geothermal fields along the Kenya Rift System. The figure is re-used without modification and with permission from [PERSON] et al. [5] following the [[https://creativecommons.org/licenses/by-nc-nd/3.0/us/](https://creativecommons.org/licenses/by-nc-nd/3.0/us/)]([https://creativecommons.org/licenses/by-nc-nd/3.0/us/](https://creativecommons.org/licenses/by-nc-nd/3.0/us/)) CC BY-NC-ND 3.0 license (accessed on 15 March 2024).  
ware, and the data that the cameras provide. We compare the camera results with data from a nearby weather station and a climate reanalysis dataset and discuss the system's performance so far and possible improvements.