Machine learning (ML) sensors offer a new paradigm for sensing that enables
intelligence at the edge while empowering end-users with greater control of
their data. As these ML sensors play a crucial role in the development of
intelligent devices, clear documentation of their specifications,
functionalities, and limitations is pivotal. This paper introduces a standard
datasheet template for ML sensors and discusses its essential components
including: the system's hardware, ML model and dataset attributes, end-to-end
performance metrics, and environmental impact. We provide an example datasheet
for our own ML sensor and discuss each section in detail. We highlight how
these datasheets can facilitate better understanding and utilization of sensor
data in ML applications, and we provide objective measures upon which system
performance can be evaluated and compared. Together, ML sensors and their
datasheets provide greater privacy, security, transparency, explainability,
auditability, and user-friendliness for ML-enabled embedded systems. We
conclude by emphasizing the need for standardization of datasheets across the
broader ML community to ensure the responsible and effective use of sensor
data.

本文介绍了一种标准的 ML 传感器数据表格模板，重点讨论了其必要组成部分：系统硬件，ML 模型和数据集属性，端到端性能指标以及环境影响。通过提供样例数据表格，突显了它们如何促进传感器数据在 ML 应用中的更好理解和利用，并提供了客观的度量标准以评估和比较系统性能。ML 传感器和其数据表格能够提供更好的隐私、安全、透明度、可解释性、可审计性和用户友好性。最后强调 ML 社区的数据表格需要标准化，以确保对传感器数据的负责和有效的使用。