Solve the following sql problem:
Find the longest ride on foggy day. What were the mean visibility, mean wind speed, and weather event during that ride? Also, list the coordinates and names of the start and end stations.

Schema:
SCHEMA:
- Table: station
  - Column: id
    - Samples: [2, 3, 4, 5, 6]
  - Column: name
    - Samples: [San Jose Diridon Caltrain Station, San Jose Civic Center, Santa Clara at Almaden, Adobe on Almaden, San Pedro Square]
  - Column: lat
    - Samples: [37.329732, 37.330698, 37.333988, 37.331415, 37.336721000000004]
  - Column: long
    - Samples: [-121.90178200000001, -121.888979, -121.894902, -121.8932, -121.894074]
  - Column: dock_count
    - Samples: [27, 15, 11, 19, 15]
  - Column: city
    - Samples: [San Jose, San Jose, San Jose, San Jose, San Jose]
  - Column: installation_date
    - Samples: [8/6/2013, 8/5/2013, 8/6/2013, 8/5/2013, 8/7/2013]
- Table: status
  - Column: station_id
    - Samples: [2, 2, 2, 2, 2]
  - Column: bikes_available
    - Samples: [2, 2, 2, 2, 2]
  - Column: docks_available
    - Samples: [25, 25, 25, 25, 25]
  - Column: time
    - Samples: [2013/08/29 12:06:01, 2013/08/29 12:07:01, 2013/08/29 12:08:01, 2013/08/29 12:09:01, 2013/08/29 12:10:01]
- Table: trip
  - Column: id
    - Samples: [4069, 4073, 4074, 4075, 4076]
  - Column: duration
    - Samples: [174, 1067, 1131, 1117, 1118]
  - Column: start_date
    - Samples: [8/29/2013 9:08, 8/29/2013 9:24, 8/29/2013 9:24, 8/29/2013 9:24, 8/29/2013 9:25]
  - Column: start_station_name
    - Samples: [2nd at South Park, South Van Ness at Market, South Van Ness at Market, South Van Ness at Market, South Van Ness at Market]
  - Column: start_station_id
    - Samples: [64, 66, 66, 66, 66]
  - Column: end_date
    - Samples: [8/29/2013 9:11, 8/29/2013 9:42, 8/29/2013 9:43, 8/29/2013 9:43, 8/29/2013 9:43]
  - Column: end_station_name
    - Samples: [2nd at South Park, San Francisco Caltrain 2 (330 Townsend), San Francisco Caltrain 2 (330 Townsend), San Francisco Caltrain 2 (330 Townsend), San Francisco Caltrain 2 (330 Townsend)]
  - Column: end_station_id
    - Samples: [64, 69, 69, 69, 69]
  - Column: bike_id
    - Samples: [288, 321, 317, 316, 322]
  - Column: subscription_type
    - Samples: [Subscriber, Subscriber, Subscriber, Subscriber, Subscriber]
  - Column: zip_code
    - Samples: [94114, 94703, 94115, 94122, 94597]
- Table: weather
  - Column: date
    - Samples: [8/29/2013, 8/30/2013, 8/31/2013, 9/1/2013, 9/2/2013]
  - Column: max_temperature_f
    - Samples: [74, 78, 71, 74, 75]
  - Column: mean_temperature_f
    - Samples: [68, 69, 64, 66, 69]
  - Column: min_temperature_f
    - Samples: [61, 60, 57, 58, 62]
  - Column: max_dew_point_f
    - Samples: [61, 61, 57, 60, 61]
  - Column: mean_dew_point_f
    - Samples: [58, 58, 56, 56, 60]
  - Column: min_dew_point_f
    - Samples: [56, 56, 54, 53, 58]
  - Column: max_humidity
    - Samples: [93, 90, 93, 87, 93]
  - Column: mean_humidity
    - Samples: [75, 70, 75, 68, 77]
  - Column: min_humidity
    - Samples: [57, 50, 57, 49, 61]
  - Column: max_sea_level_pressure_inches
    - Samples: [30.07, 30.05, 30.0, 29.96, 29.97]
  - Column: mean_sea_level_pressure_inches
    - Samples: [30.02, 30.0, 29.96, 29.93, 29.94]
  - Column: min_sea_level_pressure_inches
    - Samples: [29.97, 29.93, 29.92, 29.91, 29.9]
  - Column: max_visibility_miles
    - Samples: [10, 10, 10, 10, 10]
  - Column: mean_visibility_miles
    - Samples: [10, 10, 10, 10, 10]
  - Column: min_visibility_miles
    - Samples: [10, 7, 10, 10, 6]
  - Column: max_wind_Speed_mph
    - Samples: [23, 29, 26, 25, 23]
  - Column: mean_wind_speed_mph
    - Samples: [11, 13, 15, 13, 12]
  - Column: max_gust_speed_mph
    - Samples: [28, 35, 31, 29, 30]
  - Column: precipitation_inches
    - Samples: [0, 0, 0, 0, 0]
  - Column: cloud_cover
    - Samples: [4, 2, 4, 4, 6]
  - Column: events
    - Samples: [, , , , ]
  - Column: wind_dir_degrees
    - Samples: [286, 291, 284, 284, 277]
  - Column: zip_code
    - Samples: [94107, 94107, 94107, 94107, 94107]

SELECT T3.mean_visibility_miles, T3.mean_wind_speed_mph, T3.events, T1.lat, T1.long , T2.start_station_name, T2.end_station_name FROM station AS T1 INNER JOIN trip AS T2 ON T2.start_station_name = T1.name INNER JOIN weather AS T3 ON T3.zip_code = T2.zip_code WHERE T3.events = 'Fog' ORDER BY T2.duration DESC LIMIT 1