Estimating Bus Cross-Sectional Flow Based on Machine Learning Algorithm Combined with Wi-Fi Probe Technology.

With expansion of city scale, the issue of public transport systems will become prominent. For single-swipe buses, the traditional method of obtaining section passenger flow is to rely on surveillance video identification or manual investigation. This paper adopts a new method: collecting wireless signals from mobile terminals inside and outside the bus by installing six Wi-Fi probes in the bus, and use machine learning algorithms to estimate passenger flow of the bus. Five features of signals were selected, and then the three machine learning algorithms of Random Forest, K-Nearest Neighbor, and Support Vector Machines were used to learn the data laws of signal features. Because the signal strength was affected by the complexity of the environment, a strain function was proposed, which varied with the degree of congestion in the bus. Finally, the error between the average of estimation result and the manual survey was 0.1338. Therefore, the method proposed is suitable for the passenger flow identification of single-swiping buses in small and medium-sized cities, which improves the operational efficiency of buses and reduces the waiting pressure of passengers during the morning and evening rush hours in the future.

Construction of Heterostructure between Ni17W3 and WO2 to Boost the Hydrogen Oxidation Reaction in Alkaline Medium.

The inferior intrinsic performance of Ni-based catalysts for the hydrogen oxidation reaction (HOR) in an alkaline medium seriously restricts the utilization of emerging anion-exchange membrane fuel cells (AEMFCs). This is because the hydrogen and hydroxyl binding energies on Ni need to be optimized. Although electrocatalysts obtained by alloying Ni with Mo or W reportedly exhibit enhanced activity, they are still far from industrial requirements based on unbalanced HBE and OHBE. Herein, we report to further enhance alkaline HOR activity by constructing a heterostructure between NiW alloy and metal oxide (Ni17W3/WO2), which is synthesized through solvothermal treatment combined with annealing. The as-fabricated reduced graphene oxide (rGO)-supported Ni17W3/WO2 (Ni17W3/WO2/rGO) exhibits state-of-the-art catalytic activity (current density of 2.9 mA cm-2 at 0.1 V vs RHE), faster kinetics (geometric kinetics current density of 4.0 mA cm-2 that can be comparable to Pt/C), and high stability (maintaining the current density for more than 80 h) toward HOR in alkaline media. The detailed characterizations reveal that the charge transfer across the boundary arising from constructing the as-prepared heterostructure tunes the electronic structures, ultimately facilitating the HOR process.