System-level telemetry is fundamental to modern remote monitoring, predictive maintenance, and AI-driven infrastructure optimisation. Existing telemetry encodings such as JSON, JSON Lines, CBOR, and Protocol Buffers were designed for high-bandwidth, always-online environments. They impose significant overhead when deployed in bandwidth-constrained networks common across Sub-Saharan Africa, rural enterprise deployments, and unstable LAN environments. This paper introduces MTS-1 (Magenta Telemetry Standard v1), a novel delta-encoded binary telemetry format designed for offline-first system monitoring, LAN-assisted proxy delivery, and energy-efficient IoT-to-server transmission. We compare MTS-1 against JSON, JSON Lines, CBOR, MessagePack, and Protocol Buffers across payload size, encoding cost, network efficiency, and cost-latency performance. Synthetic benchmarking demonstrates preliminary compression improvements of up to 74.7% versus JSON and 5.4% versus MessagePack, with linear scaling characteristics across dataset sizes.

翻译：系统级遥测是现代远程监控、预测性维护和AI驱动基础设施优化的基础。现有的遥测编码格式，如JSON、JSON Lines、CBOR和Protocol Buffers，是为高带宽、始终在线的环境设计的。当部署在撒哈拉以南非洲地区、农村企业部署和不稳定局域网环境中常见的带宽受限网络时，它们会带来显著的开销。本文介绍了MTS-1（Magenta Telemetry Standard v1），这是一种新颖的差分编码二进制遥测格式，专为离线优先系统监控、局域网辅助代理传输和节能的物联网到服务器传输而设计。我们比较了MTS-1与JSON、JSON Lines、CBOR、MessagePack和Protocol Buffers在有效载荷大小、编码成本、网络效率以及成本-延迟性能方面的表现。合成基准测试显示，与JSON相比，其初步压缩改进高达74.7%；与MessagePack相比，改进达5.4%，并且在不同数据集大小下表现出线性扩展特性。