Artificial Neural Networks are increasingly integrated into critical infrastructures in Europe, enhancing their efficiency and functionality. However, this presents significant ethical and technical challenges, related to privacy, fairness, transparency, and accountability. We address this by proposing a trustworthy AI benchmark (TAIB), which incorporates both quantitative and qualitative aspects, towards responsible sensor networks. Quantitatively, TAIB evaluates measurable metrics, e.g., accuracy, latency, and robustness. Qualitatively, TAIB tackles unforeseen uncertainties through verifiability, explainability, and transparency, fostering accountability as digital trust. With a smart grid case study we define countermeasures, including validation and verification of ANN models, to be translated into drafted TAIB metrics, for reporting ANNs accountability as a human-oriented digital trust service, converging with regulations like EU AI Act and OIML-D31 to serve the public good, while contributing to a sustainable future. Finally, discussion and conclusion sections present potential further work, inviting others to participate in this AI ethics challenge.