Green Logistics InfoBot: A Comprehensive Carbon Footprint Information and Guidance System.
DOI:
https://doi.org/10.14456/jiist.2025.3Keywords:
Green Logistics, Carbon Footprint Management, Artificial Intelligence, Sustainable logistics, Thailand Logistics, Environmental Information Systems, Supply Chain SustainabilityAbstract
Thailand's logistics sector contributes approximately 30% of the country's total carbon emissions, presenting a critical challenge for achieving the nation's carbon neutrality target by 2050. This research proposes the development of the Green Logistics InfoBot Framework, an AI-powered comprehensive information and guidance system designed to address the significant knowledge gap between environmental awareness and practical carbon reduction implementation in Thailand's logistics industry.
The proposed framework integrates five interconnected core components to deliver intelligent environmental guidance: (1) Data Integration Layer incorporating real-time logistics emission databases, fuel consumption metrics, and Thai government regulatory frameworks including the Thailand Taxonomy for Sustainable Activities and Royal Decree on Environmentally Friendly Vehicles; (2) Intelligent Processing Framework featuring multilingual natural language processing (Thai-English), machine learning algorithms for personalized carbon reduction strategies, and predictive analytics optimized for Southeast Asian supply chain patterns; (3) Knowledge Management System containing comprehensive repositories of Thailand's green logistics regulations, best practice databases from successful Thai enterprises, and integration protocols with the country's expanding electric vehicle infrastructure under the EV 30@30 policy; (4) User Interaction Interface providing conversational AI chatbot capabilities, interactive carbon footprint calculators tailored to Thai logistics operations, route optimization considering Thailand's unique geographical constraints, and multi-platform accessibility for diverse operator scales from small freight forwarders to major distribution centers; and (5) Decision Support Framework delivering evidence-based recommendations aligned with Thai regulatory requirements, cost-benefit analysis incorporating local fuel prices and carbon credit market dynamics, and performance tracking systems compatible with existing Thai logistics management platforms.
The framework addresses specific challenges within Thailand's logistics ecosystem, including fragmented environmental information, complex regulatory compliance requirements, limited access to carbon reduction technologies among small-medium enterprises, and insufficient integration between traditional logistics operations and emerging sustainable practices. By leveraging artificial intelligence and localized content delivery, the system aims to democratize access to carbon footprint management tools across Thailand's diverse logistics sector, from international shipping companies in Laem Chabang Port to regional distribution networks serving rural provinces.
This research contributes to Thailand's sustainable development goals by proposing a scalable, technology-driven solution that bridges the critical information gap between environmental policy and operational implementation. The framework's design prioritizes practical applicability within Thailand's existing logistics infrastructure while supporting the transition toward sustainable logistics systems aligned with national carbon neutrality commitments and regional ASEAN sustainability initiatives.
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