Abstract
The devastating floods that struck Kerala in August 2018 caused widespread destruction, resulting in significant losses to individuals, institutions, agriculture, and public infrastructure. In order to streamline the post-flood rehabilitation and relief efforts, ThoughtRipples, swiftly developed and deployed two mobile applications. These apps facilitated comprehensive surveys of flood-affected areas, enabling the evaluation of losses to houses, shops, and enterprises. The implementation of these apps, combined with digital data processing, significantly expedited the disbursement of relief funds and enhanced transparency in the relief distribution process. This case study examines the successful utilization of technology during a crisis situation, showcasing the benefits of prompt and efficient data collection, analysis, and relief fund distribution.
Introduction
The devastating floods in Kerala in August 2018 led to massive losses across various sectors. Recognizing the need for a streamlined and efficient approach to assess the damage and plan relief measures, ThoughtRipples developed two mobile apps within a remarkably short timeframe. These apps aimed to facilitate accurate data collection, analysis, and evaluation of losses caused by the floods.
Solution Development
ThoughtRipples swiftly developed two mobile applications to address the specific needs of the post-flood scenario. The first app focused on surveying flood-affected areas to evaluate losses to houses, shops, and enterprises. The app utilized data server APIs provided by Information Kerala Mission (IKM) and equipped more than 21,152 government-assigned volunteers with the necessary tools to conduct surveys. Over 324,782 households were surveyed, and crucial data, including photographs and GPS coordinates, were collected. This initial app development was completed within an impressive two-day timeframe.
Enhanced Functionality
Building upon the success of the initial app, ThoughtRipples further enhanced the Rebuild Kerala App to meet advanced requirements during the floods of 2019. The app included features for the verification of affected households and the processing of appeals and grievances by government officials. This additional functionality aimed to facilitate the efficient processing and disbursement of relief funds.
Results and Efficiency Achieved
The prompt utilization of technology during the crisis situation in Kerala yielded several positive outcomes. ThoughtRipples successfully developed and deployed the mobile app within 48 hours, meeting all the data collection requirements of the government. The digital means employed for data processing and verification significantly improved the transparency and speed of disbursement of relief funds. By leveraging the data collected during the two flood periods, the government was able to create a heat map highlighting the most flood-prone areas in the state, aiding in future disaster planning and mitigation efforts.
Absent Solution Scenario
In the absence of the mobile apps and digital data processing, the documentation of losses to citizens would have been a challenging and time-consuming task. This could have resulted in delays, errors, and conflicts in meeting the government’s commitment to releasing flood relief funds to the victims. The absence of efficient technology-driven solutions would have hindered the overall relief and rehabilitation process, potentially exacerbating the suffering of those affected by the floods.
Conclusion
ThoughtRipples’ implementation of mobile apps for surveying flood-affected areas in Kerala proved instrumental in streamlining the evaluation of losses and expediting the disbursement of relief funds. By leveraging technology, the government was able to ensure transparency, accuracy, and efficiency in its relief efforts. The success of this initiative highlights the crucial role of technology in crisis situations, showcasing how prompt utilization of digital tools can significantly aid in planning, processing, and implementing relief and rehabilitation activities.