Integral Chatbot Solution for Efficient Incident Management and Emergency or Disaster Response: Optimizing Communication and Coordination Cover Image

Integral Chatbot Solution for Efficient Incident Management and Emergency or Disaster Response: Optimizing Communication and Coordination
Integral Chatbot Solution for Efficient Incident Management and Emergency or Disaster Response: Optimizing Communication and Coordination

Author(s): Oscar Peña-Cáceres, Anthony Tavara-Ramos, Teofilo Correa-Calle, Manuel More-More
Subject(s): Business Economy / Management, Energy and Environmental Studies
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Population; emergency; disaster; alert system; chatbot

Summary/Abstract: Climate change, with its unstable and dynamic weather phenomena, has a significant impact on the city of Piura, Peru, making it particularly vulnerable to the El Niño phenomenon. The limited technological infrastructure for communication between local authorities and the community has resulted in decisions that are unacceptable to the population. In order to address this gap and improve coordination during emergency or disaster situations, it is proposed to develop a specialized chatbot that integrates with modern platforms such as WhatsApp, Manychat, and Google Sheets. The solution was evaluated through a questionnaire and an observation guide, addressed to 30 citizens of the districts of Piura, Castilla, and Catacaos, Peru. The degree of satisfaction on the part of the users was 26.38%. In terms of the criterion of clarity, it is 26.44%. While 22.73% said that they needed coherence and fluency in conversation, Lastly, 24.45% corresponded to the level of accuracy in forwarding information and queries. The results of the study highlight the effectiveness of this solution as a digital alternative that not only optimizes incident management but also provides efficient responses and motivates citizens to be prepared through the use of modern technologies.

  • Issue Year: 13/2024
  • Issue No: 1
  • Page Range: 50-61
  • Page Count: 12
  • Language: English