Sensing Change: Measuring Cookstove Adoption with Internet-of-Things Sensors

AbstractBy 2012, the civil war in Darfur, Sudan, had been ongoing for 9 years. The war had displaced missions of people and concentrated them into camps for internally-displaced people. This put immense strain on the local availability of woody biomass used for cooking. Women are primarily responsible for collecting fuelwood, and it was estimated that a 7-hour round trip was necessary to collect sufficient firewood for 2 or 3 days, causing great physical hardship to the women and exposing them to extreme risk of sexual violence as they ventured outside the safety of the camps. The Berkeley-Darfur Stove had been demonstrated to reduce fuel use by roughly 50%. However, recall error and social-desirability bias makes evaluating stove use through surveys challenging. This case study chronicles the integration of low-cost temperature sensors into the Berkeley-Darfur Stove to measure actual use (in contrast to self-reported use), as well as the challenges associated with conducting fieldwork and processing large datasets. Based on this work, it was determined that at least 75% of the women who received the Berkeley-Darfur Stove for free actually adopted it for routine use. Additionally, it was (serendipitously) found that just the act of conducting follow-up surveys had a significant positive impact on adoption. In-person surveys were also conducted, and no correlation was found between the stated use frequency of the cookstoves and the measured use frequency (as determined by the sensors), likely due to the social-desirability bias. This work has launched a variety of ventures including the development of data processing software, improved sensor design, and—most recently—the founding of Geocene, a company focused on expanding the application of remote sensors and providing consulting for companies building Internet of Things (IoT) products.