public async Task <AnomalyServiceResponse> GetAnomalyPrediction(DailyConsumptionDetail dailyConsumptionDetail, SqlConnection sqlConnection, SqlTransaction sqlTransaction, string piServerName, bool isDailyPrediction = true)
{
string predictionDate = dailyConsumptionDetail.Timestamp.ToString("yyyy-MM-ddTHH:mm:ssZ");
if (isDailyPrediction)
{
predictionDate = dailyConsumptionDetail.Timestamp.AddDays(1).ToString("yyyy-MM-ddTHH:mm:ssZ");
}
AnomalyServiceRequest requestmodel = new AnomalyServiceRequest()
{
Inputs = new Inputs()
{
input1 = new Input1()
{
ColumnNames = new List <string> {
"Id", "AMPS_SYSTEM_AVG", "Building", "Breaker_details", "Daily_electric_cost",
"Daily_KWH_System", "Monthly_electric_cost", "Monthly_KWH_System", "PowerScout",
"Temperature", "Timestamp", "Visibility", "kW_System", "PiServerName"
},
Values = new List <List <string> >
{
new List <string>
{
"0", "0", dailyConsumptionDetail.Building, dailyConsumptionDetail.Breaker_details, "0", "0",
"0", "0",
dailyConsumptionDetail.PowerScout, dailyConsumptionDetail.Temperature.ToString(), predictionDate,
dailyConsumptionDetail.Visibility.ToString(), "0", piServerName
}
}
}
}
};
var azureMLConfigurationService = new AzureMLConfigurationService();
var predictionConfig = azureMLConfigurationService.GetPredictionConfigData(sqlConnection, sqlTransaction);
return(await AzureMLClient.CallAzureMLAsync(requestmodel, predictionConfig.AzureMlDailyPredictionApiURL, predictionConfig.AzureMlDailyPredictionApiKey));
}
/// <summary>
/// Detects the anomalies and generate alert.
/// </summary>
/// <param name="timerInfo">The timer information.</param>
/// <returns>
/// A <see cref="Task" /> representing the asynchronous operation.
/// </returns>
public static async Task ProcessAnomalyDetection([TimerTrigger("0 0 0 * * *")] TimerInfo timerInfo)
{
try
{
var alertService = new AlertService();
var meterService = new MeterService();
var requestModel = new AnomalyServiceRequest();
using (SqlConnection sqlConnection = new SqlConnection(ConfigurationSettings.DbConnectionString))
{
sqlConnection.Open();
var piServers = meterService.GetPiServerList(sqlConnection);
foreach (var piServer in piServers)
{
try
{
DateTime anomalyDetectionStartTime = piServer.PiServerCurrentDateTime.AddDays(-1).Date;
DateTime anomalyDetectionEndTime = anomalyDetectionStartTime.AddHours(24).AddSeconds(-1);
using (SqlTransaction sqlTransaction = sqlConnection.BeginTransaction())
{
var query = "SELECT PowerScout, Temperature, Timestamp, Visibility, kW_System, days, Breaker_details FROM LiveData WHERE Timestamp > @startTime AND Timestamp <= @endTime and PiServerName = @PiServerName ORDER BY Timestamp";
requestModel.GlobalParameters = new GlobalParameter();
Inputs inputs = new Inputs();
Input1 input = new Input1()
{
ColumnNames = new List <string> {
"PowerScout", "Temperature", "Timestamp", "Visibility", "kW_System", "days", "Breaker_details"
}
};
List <List <string> > values = new List <List <string> >();
using (SqlCommand selectDataCommand = new SqlCommand(query, sqlConnection, sqlTransaction))
{
selectDataCommand.Parameters.AddWithValue("@startTime", anomalyDetectionStartTime.ToString(Constants.DATE_TIME_FORMAT));
selectDataCommand.Parameters.AddWithValue("@endTime", anomalyDetectionEndTime.ToString(Constants.DATE_TIME_FORMAT));
selectDataCommand.Parameters.AddWithValue("@PiServerName", piServer.PiServerName);
using (SqlDataReader result = selectDataCommand.ExecuteReader())
{
List <string> rowValues = null;
while (result.Read())
{
rowValues = new List <string>();
rowValues.Add(SqlTypeConverter.ToString(result["PowerScout"]));
rowValues.Add(SqlTypeConverter.ToString(result["Temperature"]));
rowValues.Add(SqlTypeConverter.ToDateTime(result["Timestamp"]).ToString(Constants.DATE_TIME_FORMAT));
rowValues.Add(SqlTypeConverter.ToString(result["Visibility"]));
rowValues.Add(SqlTypeConverter.ToString(result["kW_System"]));
rowValues.Add(SqlTypeConverter.ToString(result["days"]));
rowValues.Add(SqlTypeConverter.ToString(result["Breaker_details"]));
values.Add(rowValues);
}
result.Close();
}
}
if (values.Count > 0)
{
input.Values = values;
inputs.input1 = input;
requestModel.Inputs = inputs;
var azureMLConfigurationService = new AzureMLConfigurationService();
var anomalyConfig = azureMLConfigurationService.GetAnomalyConfigData(sqlConnection, sqlTransaction);
var responseModel = await AzureMLClient.CallAzureMLAsync(requestModel, anomalyConfig.AzureMlAnomalyDetectionApiUrl, anomalyConfig.AzureMlAnomalyDetectionApiKey);
if (responseModel != null)
{
AddAnomalyToDatabase(sqlConnection, sqlTransaction, responseModel, piServer.PiServerName, anomalyDetectionStartTime, anomalyDetectionEndTime, alertService);
}
}
sqlTransaction.Commit();
}
}
catch (Exception e)
{
var errorMsg = string.Format("AnomalyDetectionJob Error : Anomaly detection failed for pi server - {0}", piServer.PiServerName);
Console.WriteLine(errorMsg);
Console.WriteLine("Error Message - {0}", e.Message);
Console.WriteLine("StackTrace - {0}", e.StackTrace);
ApplicationInsightsLogger.LogException(e, new Dictionary <string, string> {
{ "Job Error Message", errorMsg }
});
}
}
sqlConnection.Close();
}
}
catch (Exception e)
{
ApplicationInsightsLogger.LogException(e);
throw;
}
}
