Calculating an hourly average of measurements

We are assuming the input data looks like this:

  "c8y_TemperatureMeasurement": {"T": {"value": ..., "unit": "C"}},
  "time": "...",
  "source": {"id":"..."},
  "type": "c8y_TemperatureMeasurement"

To create the average (mean), we need the following parts in the module:

For example:

using com.apama.aggregates.avg; 
using com.apama.aggregates.last; 
using com.apama.cumulocity.Measurement;

monitor HourlyAvgMeasurementDeviceContext {

  event AverageByDevice {
    string source;
    float avgValue;
    string unit;

  action onload() {
    // Subscribe to Measurement.SUBSCRIBE_CHANNEL to receive all measurements

    from m in all Measurement(type="c8y_TemperatureMeasurement") within (3600.0) 
      group by m.source select
          last(m.measurements["c8y_TemperatureMeasurement"]["T"].unit)) as avgdata {
            send Measurement("", "c8y_AverageTemperatureMeasurement", avgdata.source, currentTime,
                  "T": MeasurementValue(avgdata.avgValue, avgdata.unit, new dictionary<string,any>)
              }, new dictionary<string,any>) to Measurement.SEND_CHANNEL;

Creating alarms from bit measurements

Devices often keep alarm statuses in registers and cannot interpret the meaning of alarms. In this example, we assume that a device just sends the entire register as a binary value in a measurement. A rule must identify the bits and create the respective alarm.

We create three dictionaries to map alarm text, type and severity for each of the bits, and an action to look up the value. We use -1 to indicate a default value, and replace <position> with the string form of the position.

dictionary<integer, string> positionToAlarmType := {
	0  : "c8y_HighTemperatureAlarm",
	1  : "c8y_ProcessingAlarm",
	2  : "c8y_DoorOpenAlarm",
	3  : "c8y_SystemFailureAlarm",
	-1 : "c8y_FaultRegister<position>Alaram"

dictionary<integer, string> positionToAlarmSeverity := {
	0  : "MAJOR",
	1  : "WARNING",
	2  : "MINOR",
	3  : "CRITICAL",
	-1 : "MAJOR"

dictionary<integer, string> positionToAlarmText := {
	0  : "The machine temperature reached a critical status",
	1  : "There was an error trying to process data",
	2  : "Door was opened",
	3  : "There was a critical system failure",
	-1 : "An undefined alarm was reported on position <position> in the binary fault register"

action getText(integer bitPosition, dictionary<integer, string> lookup) returns string {
	string template := lookup.getOr(bitPosition, lookup[-1]);
	return template.replaceAll("<position>", bitPosition.toString());

To analyze the binary measurement value, we will interpret it as a string value and loop through each character. The getActiveBits() function will do that and return a list of the bit positions at where the measurement had a “1”. We can then use a for loop to iterate through that:

action getBitPositions(string binaryAsText) returns sequence<integer> {
	sequence<integer> bitsSet := new sequence<integer>;
	integer i := 0;
	while i < binaryAsText.length() {
		string character := binaryAsText.substring(i, i+1);
		if character = "1" {
			bitsSet.append(binaryAsText.length() - i - 1);
	return bitsSet;

action onload() {
	// Subscribe to Measurement.SUBSCRIBE_CHANNEL to receive all measurements
	on all Measurement(type = "c8y_BinaryFaultRegister") as m {
		string faultRegister := m.measurements.getOrDefault("c8y_BinaryFaultRegister").getOrDefault("errors").value.toString();
		integer bitPosition;
		for bitPosition in getBitPositions(faultRegister) {
			Alarm alarm    := new Alarm;
			alarm.type     := getText(bitPosition, positionToAlarmType);
			alarm.severity := getText(bitPosition, positionToAlarmSeverity);
			alarm.text     := getText(bitPosition, positionToAlarmText);
			alarm.source   := m.source;
			alarm.time     := m.time;
			alarm.status   := "ACTIVE";
			send alarm to Alarm.SEND_CHANNEL;

Creating a measurement like this

    "c8y_BinaryFaultRegister": {"errors": {"value": 10110}},
    "time": "...",
    "source": {"id": "..."},
    "type": "c8y_BinaryFaultRegister"

will trigger the last statement three times.

and therefore create three alarms.

Consumption measurements

Assuming we have a sensor which measures the current fill level of something and sends the values on a regular basis to Cumulocity IoT, we can easily create additional consumption values. Calculating the absolute difference between two measurements can be useful, but it will only give you a clear view if the measurements are sent always in the same interval. Therefore, we will put the absolute difference in relation to the time difference and calculate as a per hour consumption.

We will compare the value and time difference of two adjacent measurements for a device, using a stream retaining 2 entries, and selecting the first and last timestamp and value.

using com.apama.aggregates.last;
using com.apama.aggregates.first;
using com.apama.aggregates.count;

monitor FillLevelMeasurements {

	event FillLevel {
		float firstValue;
		float firstTime;
		float lastValue;
		float lastTime;
		string source;

	action calculateConsumption(FillLevel l) returns float {
		if(l.firstTime = l.lastTime) {
			return 0.0;
		} else {
			return ((l.lastValue - l.firstValue) * 3600.0) / (l.lastTime - l.firstTime);

	action onload() {
		// Subscribe to Measurement.SUBSCRIBE_CHANNEL to receive all measurements
		from m in all Measurement(type = "c8y_WaterTankFillLevel") partition by m.source retain 2 group by m.source having count() = 2
			select FillLevel(first(m.measurements["c8y_WaterTankFillLevel"]["level"].value), first(m.time), 
							last(m.measurements["c8y_WaterTankFillLevel"]["level"].value), last(m.time), m.source) as fill {

			Measurement m := new Measurement;
			m.type := "c8y_HourlyWaterConsumption";
			m.time := currentTime;
			m.source := fill.source;
			MeasurementValue mv := new MeasurementValue;
			mv.value := calculateConsumption(fill);
			mv.unit := "l/h";
			m.measurements[m.type] := {"consumption":mv};
			send m to Measurement.SEND_CHANNEL;

Miscellaneous sample apps

Apama EPL Apps provides several sample apps which demonstrate how to use Apama EPL, for example, to query for Cumulocity IoT objects or to create alarms. You can use these samples to build your own apps.