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Automatiza la Búsqueda de Imágenes: Guía con GitHub API y Google Custom Search

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Automatiza tu Flujo de Trabajo: Búsqueda Masiva de Imágenes con GitHub API y Google Custom Search En la era del contenido digital, la capacidad de encontrar y recopilar imágenes de manera eficiente es crucial para cualquier profesional, diseñador o investigador. Sin embargo, la búsqueda manual en múltiples plataformas es un proceso tedioso y extremadamente consume tiempo. A menudo nos encontramos con la necesidad de realizar una búsqueda masiva de imágenes basadas en criterios muy específicos, superando las limitaciones de los motores de búsqueda convencionales. Este artículo está diseñado para guiarte a través de una solución avanzada, combinando la potencia de las APIs de GitHub y Google Custom Search para automatizar completamente este proceso. Dominar esta técnica no solo te ahorrará incontables horas de trabajo, sino que también elevará la calidad y la escala de tu investigación visual. Exploraremos cómo utilizar las capacidades de desarrollo de GitHub y el robusto sistema de ...

Smarter Traffic Signals Prioritize Transit and People

Smarter Traffic Signals Prioritize Transit and People
By Robert Lim

Have you ever wondered how traffic signals could better balance the needs of all road users, whether driving, bicycling, walking or taking Muni? The SFMTA is rolling out its Connected Corridor Pilot this month to use transit platform and traffic signal sensor data to inform signal timing adjustments. The pilot also aims to collect information to support transit efficiency and street safety improvements.  Traffic engineers use signal timing adjustments as a tool to prioritize the flow of travel in specific directions or for different travel modes – Muni, people walking or driving – to meet the changing demands of the road network across different timepoints in a day.

The Connected Corridors Pilot seeks to push the envelope of innovation by investing in advanced technologies, funded through a U.S. Department of Transportation (USDOT) grant. These tools will better position the city to serve the potential future needs and differing priorities of various roadway users.  At the same time, the project will implement near-term improvements to our street network to make it safer and smarter. Our goal is to provide greater mobility for all users of San Francisco streets.

The sensors are mounted on traffic signal poles and transit platforms and can classify objects by size, speed and direction at a frequency of multiple times per second.  The data collected from these sensors will serve two main purposes – prioritize transit, emergency vehicle and pedestrian flows and  build dashboards to improve our data-driven decision-making processes.

Sensor mounted on a traffic signal pole

Sensor mounted on a traffic signal pole

The pilot will take place along 3rd Street at 10 intersections in the Mission Bay neighborhood.  This corridor was selected based on the presence of upgraded traffic signal infrastructure and the opportunity to explore several operational challenges:

  • Accommodating the time needed for people walking in crosswalks on wide streets while also prioritizing an extended green light for transit
  • Reduced ability to prioritize signal timing in both directions of travel because of frequent  transit operating in both north and south directions of 3rd Street
  • High volumes of people walking and bicycling due to the presence of a hospital, research hub, waterfront and two sports facilities in the area
  • Variable waiting times for passengers to exit and enter at Muni Metro platforms impact the predicted arrivals of Muni vehicles on green lights further down the line

Muni Metro traveling on 3rd Street

Muni Metro traveling on 3rd Street

These challenges provide opportunities for innovation. The project team seeks to build and test an integrated technical solution using real-time data and advanced traffic flow algorithms. These tools can  dynamically adjust the signal phasing based on actual traffic flow conditions and the presence of people using various transportation modes.  Real-time data availability and analysis will enable more precise predictions of when the train will reach the downstream intersections so that a green light is more likely to be provided, thus reducing the amount of time people on the transit are stopped at red lights.

Sensor installation is completed with the overall project scheduled to be completed by the fall. Check the project webpage to see future updates on project status, data analysis and reports.

 



Published May 27, 2021 at 01:57PM
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