A Resilient Logistics Framework for Humanitarian Supply Chains: Integrating Predictive Analytics, IoT, and Localized Distribution to Strengthen Emergency Response Systems

Authors

  • Uchechukwu Nkechinyere Anene  Federal Capital Territory Administration, Abuja, Nigeria
  • Tosin Clement  Independent Researcher, Lagos, Nigeria

Keywords:

Humanitarian Supply Chains, Resilient Logistics, Predictive Analytics, Internet of Things (IoT), Emergency Response, Localized Distribution, Real-Time Monitoring, Disaster Preparedness, Logistics Innovation, Humanitarian Operations

Abstract

In the face of increasing global disruptions, ranging from natural disasters to public health emergencies, humanitarian supply chains require robust and adaptive strategies to ensure timely and effective delivery of aid. This paper presents a resilient logistics framework that integrates predictive analytics, Internet of Things (IoT) technologies, and localized distribution systems to enhance the responsiveness, transparency, and efficiency of humanitarian operations. The proposed framework addresses critical weaknesses in traditional humanitarian logistics, such as fragmented data flows, poor visibility, and centralized decision-making, by leveraging real-time data and decentralized networks to support rapid and informed responses. Predictive analytics is utilized to forecast demand patterns, anticipate disruptions, and allocate resources optimally based on historical data and environmental indicators. These insights enable preemptive action, reducing lead times and minimizing supply mismatches during crises. Simultaneously, IoT devices such as GPS trackers, RFID tags, and environmental sensors provide continuous monitoring of inventory, transportation conditions, and asset locations, enhancing visibility and traceability across the supply chain. These data streams are integrated into a centralized analytics dashboard, supporting real-time decision-making for logistics managers and field coordinators. Localization is a central pillar of the framework, emphasizing the development of community-level distribution hubs, local partnerships, and pre-positioned inventories. This strategy reduces dependency on distant central warehouses and improves last-mile delivery under infrastructure-constrained conditions. Case examples from recent humanitarian interventions are used to validate the effectiveness of the integrated model, demonstrating significant improvements in supply chain agility, service level, and resource utilization. The proposed resilient logistics framework fosters a proactive and data-driven approach to humanitarian supply chain management. It empowers stakeholders to respond swiftly and accurately, even in volatile and uncertain environments. By aligning digital innovation with community-based logistics solutions, the framework bridges global strategy with local action, ensuring aid reaches those in need with greater precision and speed. This research offers practical implications for humanitarian organizations, governments, and development partners aiming to build more resilient and responsive emergency logistics systems.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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2022-10-30

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Volume 8, Issue 5, September-October-2022

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Research Articles

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[1]
Uchechukwu Nkechinyere Anene, Tosin Clement, " A Resilient Logistics Framework for Humanitarian Supply Chains: Integrating Predictive Analytics, IoT, and Localized Distribution to Strengthen Emergency Response Systems" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.398-424, September-October-2022.