• Aakshun Ramesh Chatla
• Shital Pazare
• Sagar DhudhBhate
• Harsh Kamani
• Dharmendra Mishra

The Time Series Anomaly Detector is a powerful tool designed to identify unusual patterns or events within a sequence of data over time. Whether monitoring financial transactions, temperature fluctuations, or any time-dependent dataset, this app helps user spin point anomalies that may indicate irregularities or unexpected occurrences.The app employs advanced algorithms to analyze historical data and normal patterns. Users can set thresholds to define what is considered typical behavior, and the app automatically flags deviations beyond these thresholds as anomalies.One key feature of the app is its user-friendly interface, making it accessible to a broad audience, including those without extensive data science expertise. The visual representation of time series data and highlighted anomalies simplify the interpretation of results. Additionally, the app supports customizable alerts, notifying users when anomalies are detected, facilitating aprompt response.In practical terms, the Time Series Anomaly Detector finds applications in diverse fields. For instance, in finance, it can identify unusual transaction patterns that may indicate fraudulent activity. In environmental monitoring, it could detect abnormal weather patterns or sensor malfunctions. The versatility of the app makes it a valuable asset across industries were understanding and responding to anomalies in time series data are critical.In summary, the Time Series Anomaly Detector is an intuitive and efficient solution for anyone seeking to gain insights from time-dependent data by swiftly identifying and addressing anomalies.

Anomaly, Detection, Outlier, Deviation, Fraud, Unusual patterns, Fault detection.

"Time Series Anomaly Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.h311-h315, April-2024, Available :http://www.jetir.org/papers/JETIR2404738.pdf

"Time Series Anomaly Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. pph311-h315, April-2024, Available at : http://www.jetir.org/papers/JETIR2404738.pdf