Amon Dîn
Collection
A collection of datasets from the Nigerian Telecommunications Sector
•
34 items
•
Updated
•
1
Datasets:
Dataset Viewer
automation_id
stringlengths 10
10
| timestamp
timestamp[ns]date 2025-09-01 00:00:00
2025-10-01 23:59:00
| tower_id
stringlengths 8
8
| city
stringclasses 15
values | optimization_type
stringclasses 8
values | ai_model
stringclasses 4
values | ai_recommendation
stringclasses 4
values | confidence_score
float64 0.7
0.99
| action_taken
bool 2
classes | performance_before_percent
float64 60
85
| performance_after_percent
float64 60
105
| improvement_percent
float64 0
20
| energy_saved_kwh
float64 0
200
| users_impacted
int64 100
5k
| operator
stringclasses 4
values | automation_status
stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
AI00000001
| 2025-09-11T16:14:00
|
ONI-2064
|
Onitsha
|
power_optimization
|
neural_network
|
decrease
| 0.83
| true
| 82.58
| 97.32
| 14.74
| 186.49
| 1,489
|
9mobile
|
success
|
AI00000002
| 2025-09-20T17:22:00
|
ENU-2233
|
Enugu
|
fault_prediction
|
neural_network
|
decrease
| 0.8
| true
| 78.46
| 87.6
| 9.14
| 0
| 3,158
|
MTN
|
failed
|
AI00000003
| 2025-09-09T12:12:00
|
KAD-3174
|
Kaduna
|
energy_saving
|
reinforcement_learning
|
redistribute
| 0.86
| true
| 62.16
| 62.16
| 11.3
| 11.69
| 4,299
|
Glo
|
failed
|
AI00000004
| 2025-09-18T06:53:00
|
ILO-8095
|
Ilorin
|
energy_saving
|
random_forest
|
maintain
| 0.78
| true
| 80.96
| 91.26
| 10.3
| 140.33
| 4,813
|
Airtel
|
success
|
AI00000005
| 2025-09-13T10:23:00
|
KAN-3526
|
Kano
|
power_optimization
|
gradient_boosting
|
increase
| 0.83
| true
| 84.88
| 99.34
| 14.46
| 33.26
| 1,859
|
Glo
|
success
|
AI00000006
| 2025-09-26T09:48:00
|
ABU-1577
|
Abuja
|
energy_saving
|
random_forest
|
redistribute
| 0.77
| false
| 63.14
| 76.82
| 13.68
| 191
| 4,101
|
Glo
|
success
|
AI00000007
| 2025-09-24T18:17:00
|
ABE-6850
|
Abeokuta
|
spectrum_allocation
|
neural_network
|
increase
| 0.77
| true
| 63.07
| 75.11
| 12.04
| 0
| 3,153
|
Glo
|
success
|
AI00000008
| 2025-09-22T05:08:00
|
JOS-4400
|
Jos
|
spectrum_allocation
|
gradient_boosting
|
increase
| 0.9
| true
| 80.52
| 80.52
| 18.39
| 0
| 329
|
Airtel
|
success
|
AI00000009
| 2025-09-17T09:32:00
|
ABA-2238
|
Aba
|
power_optimization
|
neural_network
|
maintain
| 0.88
| true
| 66.17
| 77.02
| 10.85
| 132.68
| 1,947
|
9mobile
|
success
|
AI00000010
| 2025-09-02T12:09:00
|
ABU-5362
|
Abuja
|
capacity_planning
|
reinforcement_learning
|
increase
| 0.82
| true
| 71.51
| 84
| 12.49
| 0
| 3,535
|
9mobile
|
success
|
AI00000011
| 2025-09-05T18:54:00
|
ONI-9753
|
Onitsha
|
interference_mitigation
|
neural_network
|
decrease
| 0.98
| true
| 74.79
| 83.82
| 9.03
| 0
| 2,214
|
Airtel
|
success
|
AI00000012
| 2025-09-12T08:30:00
|
POR-4825
|
Port Harcourt
|
spectrum_allocation
|
neural_network
|
increase
| 0.8
| true
| 67.04
| 77.02
| 9.98
| 0
| 296
|
9mobile
|
success
|
AI00000013
| 2025-09-02T03:57:00
|
ENU-4674
|
Enugu
|
spectrum_allocation
|
neural_network
|
redistribute
| 0.9
| true
| 66.66
| 84.41
| 17.75
| 0
| 3,292
|
Airtel
|
partial_success
|
AI00000014
| 2025-09-25T10:03:00
|
IBA-2385
|
Ibadan
|
handover_optimization
|
neural_network
|
decrease
| 0.92
| true
| 84.1
| 84.1
| 7.72
| 0
| 133
|
9mobile
|
success
|
AI00000015
| 2025-09-08T18:13:00
|
CAL-6356
|
Calabar
|
load_balancing
|
neural_network
|
maintain
| 0.71
| true
| 68.11
| 82.6
| 14.49
| 0
| 3,310
|
Glo
|
success
|
AI00000016
| 2025-09-13T18:51:00
|
ENU-8876
|
Enugu
|
interference_mitigation
|
gradient_boosting
|
maintain
| 0.95
| true
| 63.52
| 78.14
| 14.62
| 0
| 1,792
|
Airtel
|
success
|
AI00000017
| 2025-09-22T18:55:00
|
BEN-4324
|
Benin City
|
handover_optimization
|
random_forest
|
maintain
| 0.98
| true
| 78.86
| 78.86
| 18.11
| 0
| 3,618
|
Glo
|
success
|
AI00000018
| 2025-09-11T23:44:00
|
WAR-3889
|
Warri
|
handover_optimization
|
reinforcement_learning
|
maintain
| 0.84
| true
| 70.9
| 85.02
| 14.12
| 0
| 2,110
|
MTN
|
success
|
AI00000019
| 2025-09-15T02:34:00
|
POR-9946
|
Port Harcourt
|
spectrum_allocation
|
random_forest
|
decrease
| 0.97
| true
| 79.13
| 97.14
| 18.01
| 0
| 4,968
|
Airtel
|
partial_success
|
AI00000020
| 2025-09-26T23:04:00
|
CAL-6618
|
Calabar
|
interference_mitigation
|
neural_network
|
increase
| 0.76
| true
| 82.7
| 93.74
| 0
| 0
| 3,186
|
Glo
|
success
|
AI00000021
| 2025-09-04T14:09:00
|
CAL-2715
|
Calabar
|
interference_mitigation
|
neural_network
|
maintain
| 0.89
| true
| 77.38
| 87.01
| 9.63
| 0
| 1,558
|
MTN
|
success
|
AI00000022
| 2025-09-30T20:58:00
|
ONI-2095
|
Onitsha
|
handover_optimization
|
neural_network
|
decrease
| 0.82
| false
| 65.91
| 76.28
| 10.37
| 0
| 4,463
|
Airtel
|
success
|
AI00000023
| 2025-09-03T11:25:00
|
ILO-5142
|
Ilorin
|
capacity_planning
|
neural_network
|
maintain
| 0.83
| true
| 75.83
| 88.54
| 12.71
| 0
| 1,302
|
9mobile
|
success
|
AI00000024
| 2025-09-26T12:38:00
|
POR-2708
|
Port Harcourt
|
interference_mitigation
|
random_forest
|
maintain
| 0.87
| true
| 79.02
| 91.1
| 12.08
| 0
| 2,950
|
Airtel
|
success
|
AI00000025
| 2025-09-16T15:05:00
|
ONI-9075
|
Onitsha
|
spectrum_allocation
|
neural_network
|
maintain
| 0.92
| true
| 63.51
| 72.2
| 0
| 0
| 2,108
|
9mobile
|
success
|
AI00000026
| 2025-09-16T05:39:00
|
KAD-5664
|
Kaduna
|
fault_prediction
|
gradient_boosting
|
maintain
| 0.7
| true
| 68.54
| 73.58
| 5.04
| 0
| 2,483
|
Glo
|
success
|
AI00000027
| 2025-09-26T18:45:00
|
LAG-6309
|
Lagos
|
spectrum_allocation
|
gradient_boosting
|
increase
| 0.7
| true
| 77.12
| 87.14
| 10.02
| 0
| 308
|
Airtel
|
partial_success
|
AI00000028
| 2025-09-23T22:53:00
|
POR-7721
|
Port Harcourt
|
load_balancing
|
gradient_boosting
|
decrease
| 0.75
| true
| 83.38
| 93.45
| 10.07
| 0
| 870
|
Glo
|
success
|
AI00000029
| 2025-09-15T10:28:00
|
WAR-8752
|
Warri
|
spectrum_allocation
|
neural_network
|
maintain
| 0.89
| true
| 62.78
| 67.96
| 5.18
| 0
| 4,840
|
9mobile
|
success
|
AI00000030
| 2025-09-06T23:38:00
|
IBA-3512
|
Ibadan
|
spectrum_allocation
|
neural_network
|
decrease
| 0.93
| false
| 76.82
| 90.91
| 14.09
| 0
| 4,401
|
MTN
|
success
|
AI00000031
| 2025-09-22T07:27:00
|
CAL-6438
|
Calabar
|
fault_prediction
|
random_forest
|
maintain
| 0.74
| true
| 63.98
| 79.49
| 15.51
| 0
| 3,551
|
Glo
|
partial_success
|
AI00000032
| 2025-09-12T18:29:00
|
IBA-3137
|
Ibadan
|
energy_saving
|
gradient_boosting
|
maintain
| 0.74
| true
| 84.29
| 103.06
| 18.77
| 147.16
| 917
|
Airtel
|
partial_success
|
AI00000033
| 2025-09-28T05:51:00
|
ABU-1761
|
Abuja
|
power_optimization
|
reinforcement_learning
|
decrease
| 0.93
| false
| 76.16
| 92.62
| 16.46
| 98.32
| 669
|
9mobile
|
success
|
AI00000034
| 2025-09-11T06:25:00
|
JOS-9557
|
Jos
|
power_optimization
|
neural_network
|
increase
| 0.78
| true
| 75.28
| 90.41
| 15.13
| 97.9
| 4,809
|
Glo
|
partial_success
|
AI00000035
| 2025-09-26T20:54:00
|
BEN-8657
|
Benin City
|
power_optimization
|
gradient_boosting
|
maintain
| 0.76
| true
| 81.42
| 92.81
| 11.39
| 168.76
| 4,871
|
Airtel
|
success
|
AI00000036
| 2025-09-04T10:19:00
|
LAG-3935
|
Lagos
|
spectrum_allocation
|
random_forest
|
decrease
| 0.75
| true
| 68.4
| 68.4
| 14.09
| 0
| 2,652
|
MTN
|
success
|
AI00000037
| 2025-09-13T09:34:00
|
BEN-3899
|
Benin City
|
load_balancing
|
neural_network
|
maintain
| 0.85
| false
| 64
| 64
| 16.67
| 0
| 108
|
9mobile
|
success
|
AI00000038
| 2025-09-06T04:17:00
|
KAD-7850
|
Kaduna
|
spectrum_allocation
|
neural_network
|
increase
| 0.92
| true
| 63.79
| 73.88
| 10.09
| 0
| 3,500
|
9mobile
|
failed
|
AI00000039
| 2025-09-10T12:16:00
|
KAN-9260
|
Kano
|
fault_prediction
|
gradient_boosting
|
increase
| 0.85
| true
| 81.39
| 89.8
| 8.41
| 0
| 1,896
|
9mobile
|
success
|
AI00000040
| 2025-09-18T17:12:00
|
ENU-8613
|
Enugu
|
power_optimization
|
random_forest
|
decrease
| 0.98
| true
| 64.4
| 84.28
| 19.88
| 12.78
| 1,027
|
Airtel
|
success
|
AI00000041
| 2025-09-04T04:45:00
|
ENU-1487
|
Enugu
|
capacity_planning
|
random_forest
|
increase
| 0.94
| true
| 64.7
| 79.64
| 14.94
| 0
| 2,288
|
MTN
|
success
|
AI00000042
| 2025-09-16T03:22:00
|
ABU-8410
|
Abuja
|
power_optimization
|
neural_network
|
maintain
| 0.72
| true
| 75.3
| 75.3
| 10.57
| 13.11
| 3,893
|
Glo
|
success
|
AI00000043
| 2025-09-06T06:21:00
|
KAN-4122
|
Kano
|
capacity_planning
|
reinforcement_learning
|
increase
| 0.79
| false
| 83.85
| 83.85
| 0
| 0
| 857
|
Airtel
|
success
|
AI00000044
| 2025-09-22T20:10:00
|
ABU-1044
|
Abuja
|
capacity_planning
|
neural_network
|
increase
| 0.85
| true
| 60.3
| 79.54
| 19.24
| 0
| 3,049
|
9mobile
|
partial_success
|
AI00000045
| 2025-09-03T15:38:00
|
ABU-7896
|
Abuja
|
energy_saving
|
reinforcement_learning
|
maintain
| 0.86
| true
| 82.73
| 89.75
| 7.02
| 30.58
| 2,194
|
Glo
|
success
|
AI00000046
| 2025-09-24T18:09:00
|
ILO-5839
|
Ilorin
|
energy_saving
|
random_forest
|
maintain
| 0.91
| true
| 76.11
| 91.81
| 15.7
| 90.26
| 4,075
|
9mobile
|
success
|
AI00000047
| 2025-09-10T14:39:00
|
ENU-3936
|
Enugu
|
load_balancing
|
neural_network
|
increase
| 0.85
| true
| 74.34
| 86.57
| 12.23
| 0
| 4,931
|
MTN
|
success
|
AI00000048
| 2025-09-18T22:01:00
|
BEN-9446
|
Benin City
|
fault_prediction
|
gradient_boosting
|
redistribute
| 0.71
| true
| 73.94
| 82.84
| 8.9
| 0
| 4,159
|
Glo
|
success
|
AI00000049
| 2025-09-11T13:21:00
|
WAR-2411
|
Warri
|
power_optimization
|
neural_network
|
maintain
| 0.7
| false
| 76.68
| 92
| 15.32
| 97.78
| 4,771
|
MTN
|
success
|
AI00000050
| 2025-09-02T22:34:00
|
JOS-2334
|
Jos
|
capacity_planning
|
neural_network
|
increase
| 0.74
| true
| 83.48
| 83.48
| 10.13
| 0
| 4,730
|
Glo
|
success
|
AI00000051
| 2025-09-24T18:07:00
|
CAL-6214
|
Calabar
|
energy_saving
|
neural_network
|
redistribute
| 0.86
| true
| 66.1
| 74.43
| 8.33
| 97.6
| 1,143
|
Airtel
|
success
|
AI00000052
| 2025-09-13T22:12:00
|
ONI-6467
|
Onitsha
|
interference_mitigation
|
random_forest
|
maintain
| 0.72
| true
| 72.85
| 80.67
| 7.82
| 0
| 1,672
|
9mobile
|
success
|
AI00000053
| 2025-09-10T21:05:00
|
JOS-9220
|
Jos
|
fault_prediction
|
neural_network
|
decrease
| 0.74
| false
| 70.2
| 70.2
| 14.11
| 0
| 3,898
|
Glo
|
success
|
AI00000054
| 2025-09-23T15:24:00
|
POR-7172
|
Port Harcourt
|
capacity_planning
|
neural_network
|
redistribute
| 0.82
| true
| 74.15
| 83.29
| 0
| 0
| 3,484
|
9mobile
|
success
|
AI00000055
| 2025-09-16T19:19:00
|
ABA-4100
|
Aba
|
interference_mitigation
|
neural_network
|
maintain
| 0.93
| true
| 67.5
| 82.12
| 14.62
| 0
| 3,170
|
Airtel
|
success
|
AI00000056
| 2025-09-05T11:27:00
|
ABU-4690
|
Abuja
|
spectrum_allocation
|
neural_network
|
redistribute
| 0.99
| true
| 71.72
| 89.68
| 17.96
| 0
| 511
|
Airtel
|
success
|
AI00000057
| 2025-09-30T10:17:00
|
ENU-4326
|
Enugu
|
interference_mitigation
|
gradient_boosting
|
increase
| 0.74
| true
| 78.04
| 93.98
| 15.94
| 0
| 1,532
|
Glo
|
success
|
AI00000058
| 2025-09-01T22:18:00
|
IBA-6777
|
Ibadan
|
spectrum_allocation
|
reinforcement_learning
|
maintain
| 0.91
| true
| 63.7
| 71.01
| 7.31
| 0
| 1,721
|
9mobile
|
success
|
AI00000059
| 2025-09-07T19:51:00
|
WAR-8374
|
Warri
|
fault_prediction
|
random_forest
|
increase
| 0.74
| true
| 76.25
| 82.14
| 5.89
| 0
| 1,720
|
9mobile
|
success
|
AI00000060
| 2025-09-27T06:22:00
|
WAR-5534
|
Warri
|
interference_mitigation
|
reinforcement_learning
|
maintain
| 0.86
| true
| 75.8
| 91.73
| 0
| 0
| 4,433
|
Airtel
|
success
|
AI00000061
| 2025-09-15T20:22:00
|
JOS-1097
|
Jos
|
capacity_planning
|
neural_network
|
maintain
| 0.75
| false
| 83.88
| 83.88
| 9.57
| 0
| 3,452
|
Glo
|
partial_success
|
AI00000062
| 2025-09-11T08:12:00
|
KAD-9190
|
Kaduna
|
spectrum_allocation
|
neural_network
|
increase
| 0.89
| true
| 71.85
| 81
| 9.15
| 0
| 4,288
|
9mobile
|
success
|
AI00000063
| 2025-09-10T03:28:00
|
BEN-9048
|
Benin City
|
interference_mitigation
|
random_forest
|
decrease
| 0.91
| true
| 73.31
| 90.73
| 0
| 0
| 3,732
|
MTN
|
success
|
AI00000064
| 2025-09-17T16:18:00
|
ILO-3339
|
Ilorin
|
energy_saving
|
neural_network
|
redistribute
| 0.92
| true
| 65.42
| 79.01
| 13.59
| 145.58
| 620
|
Glo
|
success
|
AI00000065
| 2025-09-03T09:53:00
|
BEN-6009
|
Benin City
|
fault_prediction
|
neural_network
|
decrease
| 0.83
| true
| 65.87
| 83.52
| 17.65
| 0
| 1,997
|
MTN
|
success
|
AI00000066
| 2025-09-16T12:58:00
|
ONI-5935
|
Onitsha
|
load_balancing
|
neural_network
|
maintain
| 0.71
| true
| 71.82
| 71.82
| 15.14
| 0
| 2,930
|
9mobile
|
success
|
AI00000067
| 2025-09-19T11:07:00
|
ENU-6677
|
Enugu
|
load_balancing
|
gradient_boosting
|
decrease
| 0.92
| true
| 84.75
| 102.61
| 17.86
| 0
| 1,182
|
Glo
|
success
|
AI00000068
| 2025-09-03T11:42:00
|
IBA-2233
|
Ibadan
|
fault_prediction
|
neural_network
|
maintain
| 0.81
| true
| 84.73
| 90
| 5.27
| 0
| 494
|
9mobile
|
success
|
AI00000069
| 2025-09-06T04:44:00
|
IBA-9136
|
Ibadan
|
handover_optimization
|
gradient_boosting
|
decrease
| 0.97
| true
| 80.42
| 94.65
| 14.23
| 0
| 3,139
|
9mobile
|
failed
|
AI00000070
| 2025-09-29T02:27:00
|
KAN-9342
|
Kano
|
spectrum_allocation
|
neural_network
|
maintain
| 0.96
| true
| 74.65
| 89.23
| 14.58
| 0
| 4,541
|
MTN
|
success
|
AI00000071
| 2025-09-12T01:07:00
|
ONI-3835
|
Onitsha
|
spectrum_allocation
|
reinforcement_learning
|
maintain
| 0.74
| true
| 70.59
| 88.14
| 17.55
| 0
| 444
|
9mobile
|
success
|
AI00000072
| 2025-09-11T12:49:00
|
ONI-2115
|
Onitsha
|
capacity_planning
|
neural_network
|
maintain
| 0.98
| true
| 64.6
| 77.47
| 12.87
| 0
| 4,737
|
9mobile
|
success
|
AI00000073
| 2025-09-22T19:27:00
|
IBA-3668
|
Ibadan
|
interference_mitigation
|
neural_network
|
maintain
| 0.95
| true
| 83.03
| 95.76
| 12.73
| 0
| 4,612
|
Airtel
|
success
|
AI00000074
| 2025-09-29T17:49:00
|
ABE-6542
|
Abeokuta
|
load_balancing
|
neural_network
|
increase
| 0.76
| true
| 71.8
| 85.76
| 13.96
| 0
| 4,043
|
Airtel
|
success
|
AI00000075
| 2025-09-24T04:19:00
|
POR-9343
|
Port Harcourt
|
spectrum_allocation
|
reinforcement_learning
|
maintain
| 0.85
| true
| 65.61
| 74.19
| 0
| 0
| 1,707
|
9mobile
|
success
|
AI00000076
| 2025-09-02T08:45:00
|
ABE-6254
|
Abeokuta
|
load_balancing
|
gradient_boosting
|
increase
| 0.92
| true
| 69.85
| 89
| 19.15
| 0
| 4,463
|
MTN
|
partial_success
|
AI00000077
| 2025-09-30T11:09:00
|
ABU-1470
|
Abuja
|
fault_prediction
|
gradient_boosting
|
redistribute
| 0.94
| true
| 73.7
| 84.58
| 0
| 0
| 4,554
|
Glo
|
success
|
AI00000078
| 2025-09-11T13:30:00
|
POR-6305
|
Port Harcourt
|
interference_mitigation
|
neural_network
|
redistribute
| 0.82
| true
| 61.05
| 79.08
| 18.03
| 0
| 3,747
|
Airtel
|
success
|
AI00000079
| 2025-09-20T10:46:00
|
ILO-4924
|
Ilorin
|
power_optimization
|
neural_network
|
maintain
| 0.83
| true
| 69.93
| 69.93
| 0
| 88.38
| 2,999
|
9mobile
|
success
|
AI00000080
| 2025-09-06T23:09:00
|
WAR-9407
|
Warri
|
energy_saving
|
gradient_boosting
|
maintain
| 0.81
| true
| 83.83
| 90.91
| 0
| 26.59
| 4,012
|
Glo
|
partial_success
|
AI00000081
| 2025-09-30T11:54:00
|
KAN-5450
|
Kano
|
power_optimization
|
gradient_boosting
|
decrease
| 0.78
| true
| 73.57
| 81.35
| 7.78
| 11.19
| 1,538
|
Glo
|
success
|
AI00000082
| 2025-09-30T19:27:00
|
ABE-2357
|
Abeokuta
|
energy_saving
|
random_forest
|
decrease
| 0.83
| true
| 74.45
| 87.02
| 12.57
| 30.85
| 743
|
9mobile
|
success
|
AI00000083
| 2025-09-25T18:09:00
|
POR-3485
|
Port Harcourt
|
fault_prediction
|
random_forest
|
maintain
| 0.95
| true
| 64.36
| 64.36
| 5.8
| 0
| 1,187
|
9mobile
|
success
|
AI00000084
| 2025-09-01T20:10:00
|
WAR-3125
|
Warri
|
handover_optimization
|
reinforcement_learning
|
decrease
| 0.93
| true
| 83.19
| 102.96
| 19.77
| 0
| 2,496
|
MTN
|
success
|
AI00000085
| 2025-09-13T02:33:00
|
POR-3721
|
Port Harcourt
|
power_optimization
|
gradient_boosting
|
increase
| 0.86
| true
| 71.11
| 80.13
| 0
| 153.32
| 3,193
|
Airtel
|
success
|
AI00000086
| 2025-09-29T11:13:00
|
ENU-1825
|
Enugu
|
handover_optimization
|
neural_network
|
increase
| 0.79
| true
| 72.08
| 72.08
| 0
| 0
| 1,150
|
Airtel
|
partial_success
|
AI00000087
| 2025-09-03T11:05:00
|
POR-7293
|
Port Harcourt
|
load_balancing
|
gradient_boosting
|
maintain
| 0.88
| true
| 77.68
| 97.39
| 19.71
| 0
| 2,532
|
MTN
|
partial_success
|
AI00000088
| 2025-09-07T10:00:00
|
BEN-2451
|
Benin City
|
fault_prediction
|
gradient_boosting
|
redistribute
| 0.72
| true
| 76.94
| 88.81
| 11.87
| 0
| 3,129
|
9mobile
|
success
|
AI00000089
| 2025-09-21T14:22:00
|
IBA-3664
|
Ibadan
|
interference_mitigation
|
random_forest
|
increase
| 0.77
| true
| 63.85
| 71.36
| 7.51
| 0
| 1,161
|
MTN
|
partial_success
|
AI00000090
| 2025-09-26T13:11:00
|
KAN-5250
|
Kano
|
handover_optimization
|
gradient_boosting
|
redistribute
| 0.96
| true
| 62.77
| 82.26
| 19.49
| 0
| 3,120
|
9mobile
|
success
|
AI00000091
| 2025-09-17T15:59:00
|
ABE-4119
|
Abeokuta
|
energy_saving
|
neural_network
|
maintain
| 0.71
| false
| 72.58
| 82.16
| 9.58
| 56.54
| 2,051
|
9mobile
|
success
|
AI00000092
| 2025-09-28T00:21:00
|
ENU-3961
|
Enugu
|
power_optimization
|
reinforcement_learning
|
increase
| 0.94
| true
| 77.93
| 93.21
| 15.28
| 52.52
| 3,309
|
Airtel
|
success
|
AI00000093
| 2025-10-01T09:28:00
|
ABE-5421
|
Abeokuta
|
energy_saving
|
random_forest
|
decrease
| 0.85
| true
| 71.56
| 80.68
| 9.12
| 61.45
| 3,657
|
Airtel
|
partial_success
|
AI00000094
| 2025-09-17T01:34:00
|
ONI-5762
|
Onitsha
|
fault_prediction
|
random_forest
|
decrease
| 0.86
| false
| 84.89
| 96.9
| 12.01
| 0
| 1,121
|
Glo
|
success
|
AI00000095
| 2025-09-26T08:41:00
|
ENU-9336
|
Enugu
|
fault_prediction
|
neural_network
|
redistribute
| 0.78
| true
| 81.73
| 99.33
| 0
| 0
| 3,987
|
Glo
|
success
|
AI00000096
| 2025-09-08T21:43:00
|
KAD-5023
|
Kaduna
|
power_optimization
|
reinforcement_learning
|
decrease
| 0.78
| true
| 64.15
| 78.45
| 14.3
| 64.89
| 4,763
|
Airtel
|
success
|
AI00000097
| 2025-09-20T19:16:00
|
CAL-5815
|
Calabar
|
capacity_planning
|
neural_network
|
maintain
| 0.8
| true
| 61.25
| 71.67
| 10.42
| 0
| 2,541
|
Glo
|
success
|
AI00000098
| 2025-09-29T11:23:00
|
WAR-1128
|
Warri
|
load_balancing
|
neural_network
|
increase
| 0.74
| true
| 74.79
| 81.28
| 6.49
| 0
| 3,309
|
9mobile
|
success
|
AI00000099
| 2025-09-12T13:55:00
|
ONI-6206
|
Onitsha
|
fault_prediction
|
gradient_boosting
|
redistribute
| 0.73
| true
| 75.19
| 91.48
| 16.29
| 0
| 2,601
|
MTN
|
partial_success
|
AI00000100
| 2025-09-14T16:08:00
|
LAG-1204
|
Lagos
|
capacity_planning
|
random_forest
|
increase
| 0.81
| true
| 82.42
| 94.99
| 12.57
| 0
| 2,767
|
Airtel
|
success
|
End of preview. Expand
in Data Studio
Artificial Intelligence Automation Dataset
Dataset Description
Self-optimizing network operations with AI recommendations and outcomes
Dataset Information
- Category: Emerging and Advanced
- Format: CSV, Parquet
- Rows: 150,000
- Columns: 16
- Date Generated: 2025-10-05
- Location:
data/artificial_intelligence_automation_dataset/
Schema
| Column | Type | Sample Values |
|---|---|---|
automation_id |
String | AI00000001 |
timestamp |
Datetime | 2025-09-11 16:14:00 |
tower_id |
String | ONI-2064 |
city |
String | Onitsha |
optimization_type |
String | power_optimization |
ai_model |
String | neural_network |
ai_recommendation |
String | decrease |
confidence_score |
Float | 0.83 |
action_taken |
Boolean | True |
performance_before_percent |
Float | 82.58 |
performance_after_percent |
Float | 97.32 |
improvement_percent |
Float | 14.74 |
energy_saved_kwh |
Float | 186.49 |
users_impacted |
Integer | 1489 |
operator |
String | 9mobile |
automation_status |
String | success |
Sample Data
automation_id timestamp tower_id city optimization_type ai_model ai_recommendation confidence_score action_taken performance_before_percent performance_after_percent improvement_percent energy_saved_kwh users_impacted operator automation_status
AI00000001 2025-09-11 16:14:00 ONI-2064 Onitsha power_optimization neural_network decrease 0.83 True 82.58 97.32 14.74 186.49 1489 9mobile success
AI00000002 2025-09-20 17:22:00 ENU-2233 Enugu fault_prediction neural_network decrease 0.80 True 78.46 87.60 9.14 0.00 3158 MTN failed
AI00000003 2025-09-09 12:12:00 KAD-3174 Kaduna energy_saving reinforcement_learning redistribute 0.86 True 62.16 62.16 11.30 11.69 4299 Glo failed
Nigerian Context
This dataset incorporates authentic Nigerian telecommunications characteristics:
- Geographic Coverage: Major Nigerian cities including Lagos, Abuja, Kano, Port Harcourt, Ibadan
- Operators: MTN, Airtel, Glo, 9mobile with realistic market shares
- Phone Numbers: Nigerian format (+234 prefixes)
- Currency: Nigerian Naira (NGN)
- Time Zone: West Africa Time (WAT, UTC+1)
- Network Types: 2G, 3G, 4G, 5G distribution
File Formats
CSV
data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.csv
Parquet (Recommended)
data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.parquet
Loading the Dataset
Python (Pandas)
import pandas as pd
# Load CSV
df = pd.read_csv('data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.csv')
# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.parquet')
Python (PyArrow)
import pyarrow.parquet as pq
# Load Parquet
table = pq.read_table('data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.parquet')
df = table.to_pandas()
License
MIT License - For educational and research purposes
Citation
Nigerian Telecom Datasets - Artificial Intelligence Automation Dataset
Generated: 2025-10-05
Category: Emerging and Advanced
Rows: 150,000
Related Datasets
This dataset is part of the Nigerian Telecom Datasets collection, which includes 34 datasets covering network performance, customer behavior, financial transactions, infrastructure, geospatial data, customer experience, and emerging technologies.
- Downloads last month
- 20
Size of downloaded dataset files:
4.07 MB
Size of the auto-converted Parquet files:
4.07 MB
Number of rows:
150,000