Solve the following sql problem:
Which bicycle is the least used bike. Check if the start and end station are from the same city and calculate the total duration travelled by the bicycle in hours for a trip made within the same city.

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 T2.bike_id, T2.start_station_name, T2.end_station_name, T1.city , CAST(T2.duration AS REAL) / 3600 FROM station AS T1 INNER JOIN trip AS T2 ON T1.name = T2.start_station_name GROUP BY T2.bike_id ORDER BY COUNT(T2.id) DESC LIMIT 1