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Smart farming platforms are frequently conceived around persistent connectivity, modern devices, scalable cloud services, specialized technical support, and the financial capacity to adopt integrated digital systems. These assumptions may not hold in smallholder and connectivity-constrained agricultural settings, where infrastructure gaps, uneven digital skills, limited advisory access, maintenance difficulties, data costs, language diversity, and uncertain platform governance shape whether digital services are usable or sustainable. This article develops a conceptual design science framework for low-resource smart farming platforms. The framework links problem relevance, contextual requirement definition, design principles, platform artifact logic, implementation conditions, evaluation needs, feedback, and framework updating. It focuses on affordability, transparent costs, incremental adoption, modular architecture, interoperability, offline-first operation, low-bandwidth communication, local usability, accessible interaction, advisory integration, maintenance capacity, farmer data control, and trust. The proposed approach treats smallholders as heterogeneous users operating within diverse production systems, infrastructures, institutions, and knowledge networks. Platform functions are therefore organized as configurable responses to identified conditions rather than as a universal technology package. The principal contribution is a structured design science logic for translating low-resource agricultural problems into bounded platform requirements and evaluable conceptual artifacts. The framework can guide platform design and research planning, but it does not independently demonstrate affordability, inclusion, adoption, scalability, sustainability, operational safety, or deployment readiness. These outcomes require local usability assessment, affordability analysis, governance review, maintenance evaluation, implementation research, and field validation involving intended users and supporting institutions.