Publicação
Optimizing IoT Device Fleets: Strategies for Effective Management, Monitoring, and Maintenance
| Resumo: | This dissertation is written in the context of working at company that provide end-to-end solutions for Smart Lockers. This dissertation addresses the challenge of optimizing the maintenance and monitoring of IoT device fleets, a complex issue given the nature and widespread use of IoT technology. The core approach involves developing a Linux-based application suite designed to streamline data retrieval and device management processes, with minimal maintenance personnel intervention. Key innovations include an Automated Triage System for real-time problem analysis, a Resolution System for data consistency, and integrated Issue Management and Alerts Systems for proactive maintenance. This solution significantly reduces device downtime and enhances fleet operational efficiency, offering a robust, user-friendly approach to IoT fleet management. The work aims to set a new standard in IoT fleet monitoring, addressing scalability and reliability challenges, and contributing to the field’s advancement. |
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| Autores principais: | Denisov, Alexander |
| Assunto: | IoT Fleet Management Predictive Maintenance Linux-based IoT Solutions Automated Triage Systems Data Integrity in IoT Local Device Management |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This dissertation is written in the context of working at company that provide end-to-end solutions for Smart Lockers. This dissertation addresses the challenge of optimizing the maintenance and monitoring of IoT device fleets, a complex issue given the nature and widespread use of IoT technology. The core approach involves developing a Linux-based application suite designed to streamline data retrieval and device management processes, with minimal maintenance personnel intervention. Key innovations include an Automated Triage System for real-time problem analysis, a Resolution System for data consistency, and integrated Issue Management and Alerts Systems for proactive maintenance. This solution significantly reduces device downtime and enhances fleet operational efficiency, offering a robust, user-friendly approach to IoT fleet management. The work aims to set a new standard in IoT fleet monitoring, addressing scalability and reliability challenges, and contributing to the field’s advancement. |
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Atividades financiadas
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