Predictive analytics technique based on hybrid sampling to manage unbalanced data in smart cities Article Swipe
Ayushi Chahal
,
Preeti Gulia
,
Nasib Singh Gill
,
Mohammad Yahya
,
Mohd Anul Haq
,
Mohammed A. Aleisa
,
Abdullah M. Al‐Enizi
,
Arfat Ahmad Khan
,
Piyush Kumar Shukla
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.heliyon.2024.e39275
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.heliyon.2024.e39275
A smart city is deemed smart enough because it has the capability to make decisions on its own. Artificial intelligence needs a lot of data from the physical world to make correct decisions. IoT sensor devices collect data from the surroundings, which is further used for predictive analytics. Collected data may be balanced or imbalanced. Unbalanced data used for decision-making without any pre-processing may lead to ravaging results. This paper proposes a novel predictive analytical technique to manage unbalanced data. A pipeline is designed using Principal Component Analysis (PCA), a hybrid sampling method, and a Machine Learning (ML) prediction method. SMOTE + ENN, a hybrid data balancing method, is used to specify imbalanced data to a balanced state. ML method is applied to form clusters and make predictions over the dataset. A large Smart City IoT dataset having 4,05,184 records has been used in this study. The proposed technique is used to predict the presence of a person in the vicinity of IoT devices. Evaluation parameters such as accuracy, precision, recall, F1-score, and Area Under Curve (AUC)/Receiver Operating Characteristic (ROC) curve are used to evaluate the proposed approach. Accuracy, Precision, Recall, F1-score, and AUC obtained using the proposed technique for cluster 0 are 0.79, 1.0, 0.79, 0.87, and 0.88 and for cluster 1 are 0.86 0.99, 0.86, 0.92, and 0.92, respectively. In view of the encouraging results, the proposed technique may prove to be a good choice to help in decision-making in different application domains in real life.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.heliyon.2024.e39275
- OA Status
- gold
- Cited By
- 1
- References
- 59
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404258861Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.heliyon.2024.e39275Digital Object Identifier
- Title
-
Predictive analytics technique based on hybrid sampling to manage unbalanced data in smart citiesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-12Full publication date if available
- Authors
-
Ayushi Chahal, Preeti Gulia, Nasib Singh Gill, Mohammad Yahya, Mohd Anul Haq, Mohammed A. Aleisa, Abdullah M. Al‐Enizi, Arfat Ahmad Khan, Piyush Kumar ShuklaList of authors in order
- Landing page
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https://doi.org/10.1016/j.heliyon.2024.e39275Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.heliyon.2024.e39275Direct OA link when available
- Concepts
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Analytics, Predictive analytics, Data science, Sampling (signal processing), Computer science, Big data, Data analysis, Data mining, Telecommunications, DetectorTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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59Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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