A weather drone (100) comprising: a first sensor (101) configured to repeatedly measure one or more parameters indicative of weather; a memory (103) coupled to the first sensor (101) and configured to store data recorded by the first sensor (101), the data comprising a series of repeatedly measured parameters; and a processor (104) coupled to the first sensor (104) and the memory (103). The processor (104) is configured to analyse the data as it is being recorded by the first sensor (101), and determine if the data exceeds a first threshold value and/or falls below a second threshold value. If the processor (104) determines that the data exceeds the first threshold value and/or falls below the second threshold value on at least one occasion, the processor (104) is configured to prevent the storage of further data from the first sensor (101) in the memory (102).

A weather drone (100) comprising: a first sensor (101) configured to repeatedly measure one or more parameters indicative of weather; a memory (103) coupled to the first sensor (101) and configured to store data recorded by the first sensor (101), the data comprising a series of repeatedly measured parameters; and a processor (104) coupled to the first sensor (104) and the memory (103). The processor (104) is configured to analyse the data as it is being recorded by the first sensor (101), and determine if the data exceeds a first threshold value and/or falls below a second threshold value. If the processor (104) determines that the data exceeds the first threshold value and/or falls below the second threshold value on at least one occasion, the processor (104) is configured to prevent the storage of further data from the first sensor (101) in the memory (102).

A method is provided for analyzing a monitoring signal from a sensing system to determine an alarm condition, where the monitoring signal is provided as a stream of digital values which are analyzed using a frequency-based or time-based algorithm to generate a plot of elements, applying a delta to each element of the plot of elements to adjust sensitivity thereof to provide a threshold and comparing a plurality of the elements of the stream with the threshold and triggering the alarm condition in the event that the threshold is exceeded; where the algorithm is changed in different time periods in response to ambient conditions of the environment determined for those time periods.

A method is provided for analyzing a monitoring signal from a sensing system to determine an alarm condition, where the monitoring signal is provided as a stream of digital values which are analyzed using a frequency-based or time-based algorithm to generate a plot of elements, applying a delta to each element of the plot of elements to adjust sensitivity thereof to provide a threshold and comparing a plurality of the elements of the stream with the threshold and triggering the alarm condition in the event that the threshold is exceeded; where the algorithm is changed in different time periods in response to ambient conditions of the environment determined for those time periods.

A method for predicting variables of interest related to a system includes collecting one or more sensor streams over a time period from sensors in the system and generating one or more anomaly streams for the time period based on the sensor streams. Values for variables of interest for the time period are determined based on the sensor streams and the anomaly streams. Next, a time-series predictive algorithm is applied to the (i) the sensor streams, (ii) the anomaly streams, and (iii) the values for the variables of interest to generate a model for predicting new values for the variables of interest. The model may then be used to predict values for the variables of interest at a time within a new time period based on one or more new sensor streams.

A modified version of a MEMS self-test procedure is presented that can be used to detect the amplitude and frequency of an external vibration from an ambient environment. The method implements processing circuitry that correlates an output sense signal, s(t), with a plurality of periodic signal portions and a plurality of shifted periodic signal portions to generate a plurality of correlation values. A frequency associated with the external vibration is determined based on the plurality of correlation values.

There is provided a system for determining multiple baselines for detecting events in a conduit. The system comprises an optical fiber interrogator for interrogating optical fiber; and one or more processors communicative with the optical fiber interrogator and memory having stored thereon computer program code configured, when executed by the one or more processors, to cause the one or more processors to perform a method. The method comprises, for each of multiple channels of the conduit, each channel comprising a portion of the conduit: obtaining phase data for the channel, the phase data being obtained by causing the optical fiber interrogator to interrogate optical fiber positioned alongside the conduit; and determining one or more baselines from the phase data. As a result, events in the conduit may be detected with fewer false positives.

There is provided a system for determining multiple baselines for detecting events in a conduit. The system comprises an optical fiber interrogator for interrogating optical fiber; and one or more processors communicative with the optical fiber interrogator and memory having stored thereon computer program code configured, when executed by the one or more processors, to cause the one or more processors to perform a method. The method comprises, for each of multiple channels of the conduit, each channel comprising a portion of the conduit: obtaining phase data for the channel, the phase data being obtained by causing the optical fiber interrogator to interrogate optical fiber positioned alongside the conduit; and determining one or more baselines from the phase data. As a result, events in the conduit may be detected with fewer false positives.

A temperature monitoring apparatus includes: a calculator configured to calculate a temperature monitoring waveform by a first-order lag function based on an elapsed time from a start of a temperature change from a first temperature to a second temperature, and a time constant calculated based on a locus of the temperature change; and a monitor configured to monitor a temperature changing from the first temperature to the second temperature based on the temperature monitoring waveform calculated by the calculator.

A temperature monitoring apparatus includes: a calculator configured to calculate a temperature monitoring waveform by a first-order lag function based on an elapsed time from a start of a temperature change from a first temperature to a second temperature, and a time constant calculated based on a locus of the temperature change; and a monitor configured to monitor a temperature changing from the first temperature to the second temperature based on the temperature monitoring waveform calculated by the calculator.