Bluetooth Low Energy (BLE) advertising network has been widely employed in various monitoring applications, where advertiser sensors update their time triggered (TT) or event triggered (ET) status in an advertising mode to a continuously scanning central scanner. This paper addresses the problem of minimizing the age of information (AoI) for monitoring over a BLE advertising network. Firstly, we propose a packet error rate-conditioned AoI model and derive the average Aol and peak AoI (PAol) in closed form. It is found that the conditional average Aol and PAol for TT traffic are smaller than those for ET traffic at the same traffic rate, λ. Additionally, when λ exceeds the advertising rate, these metrics are further derived in closed form under a zero-waiting policy, ensuring that fresh status is available at each advertising event. Secondly, we formulate two optimization problems aimed at minimizing the average Aol and PAol under zero-waiting policy, constrained by the advertising intervalTa. To minimize the average Aol, we propose two algorithms to compute the optimal exact and approximate values ofTa, utilizing a proposed bisection method and a derived approximate closed-form solution. To minimize the PAol, we also derive a closed-form solution, which is found sharing a similar structure to our derived approximate solution for minimizing the average AoI. Extensive simulation results demonstrate the accuracy of the proposed AoI model and the derived optimal solutions.