The dataset deposited here was prepared under the EPSRC-funded Humanitarian Engineering and Energy for Displacement research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. As part of the project, we deployed Lantern Monitoring Systems in Nyabiheke camp, Rwanda. The aim was to (a) evaluate lantern usage pattern – static or mobile (b) evaluate lantern charge and discharge pattern to understand consumption behaviour. The mobile lantern monitors comprise of a D.light S30 solar lantern fitted with an Arduino-based monitoring device. The most integral part of the device is the Arduino MKR GSM 1400 board connected to an ADXL345 inertial motion unit sensor. The ADXL is used to generate activity and freefall interrupts based on acceleration readings when the lantern is in use. These interrupts are, in turn, processed to calculate the step count of the user. Additionally, the voltage of lantern battery is measured using an in-house designed voltage monitor to evaluate the discharging and charging patterns. The updated values of step count, rate of change of steps and device and lantern battery voltage are stored only if a significant change in the step count is detected. The device is packaged within the lantern casing and powered through a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh. The study was conducted in 2 phases. In phase 1 (03 July 2019 to 30 September 2019), data was collected from 60 lanterns and stored locally on SD card as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. Moreover, several incidents of theft and device failures were reported leading to loss of data. In phase 2 (09 October 2019 to 18 December 2019), the design of lantern monitors was modified to fix these issues. The data was collected from 54 lanterns data and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board and internal watchdog timer was used to reset the device in case of failures. While certain failures persisted, the data yield was considerably higher than phase 1 of the study. The data from both phases of study is deposited here along with the metadata.