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edgetelemetrics/advanced-analytics
==================================

Advanced Analytics library for sensor data

08↑2900%PHP

Since Jul 28Pushed todayCompare

[ Source](https://github.com/lucasnetau/advanced-analytics)[ Packagist](https://packagist.org/packages/edgetelemetrics/advanced-analytics)[ RSS](/packages/edgetelemetrics-advanced-analytics/feed)WikiDiscussions main Synced today

READMEChangelogDependenciesVersions (1)Used By (0)

Advanced Analytics
==================

[](#advanced-analytics)

PHP library for real-time feature detection on sensor data streams. Computes statistical features from raw measurements and applies a suite of detectors to identify trends, anomalies, process shifts, and sensor health issues.

Requirements
------------

[](#requirements)

- PHP 8.4+

Installation
------------

[](#installation)

```
composer require edgetelemetrics/advanced-analytics
```

Usage
-----

[](#usage)

### Computing Features

[](#computing-features)

`FeatureCalculator` computes rolling statistics, regression, EMA, and control limits from raw values:

```
use EdgeTelemetrics\AdvancedAnalytics\FeatureCalculator;

$calc = new FeatureCalculator();

// Feed measurements one at a time
$features = $calc->compute(20.15);
// Returns: ['raw' => 20.15, 'sma3' => ..., 'mean24h' => ..., 'regression_slope' => ..., ...]
```

### Running Detectors

[](#running-detectors)

Each detector implements `DetectorInterface` and receives a `FeatureVector`:

```
use EdgeTelemetrics\AdvancedAnalytics\Features\FeatureVector;
use EdgeTelemetrics\AdvancedAnalytics\Detector\TrendDetector;

$detector = new TrendDetector();

$features['sensor_id'] = 'sensor-1';
$features['datetime'] = '2025-03-01T00:00:00Z';
$features['regression_slope'] = 0.15;
$features['regression_r2'] = 0.85;
$features['direction'] = 1;
$features['stddev'] = 0.5;

$findings = $detector->process(new FeatureVector($features));

foreach ($findings as $finding) {
    echo $finding->getFinding() . ': ' . $finding->getState()->value;
    // "trending_up: pending"
}
```

### Processing a Stream

[](#processing-a-stream)

```
use EdgeTelemetrics\AdvancedAnalytics\FeatureCalculator;
use EdgeTelemetrics\AdvancedAnalytics\Detector\{EWMADetector, CUSUMDetector, SpikeDetector};

$calc = new FeatureCalculator();
$detectors = [new EWMADetector(), new CUSUMDetector(), new SpikeDetector()];

foreach ($measurements as $m) {
    $features = $calc->compute($m['value']);
    $features['sensor_id'] = $m['sensor_id'];
    $features['datetime'] = $m['datetime'];

    $vector = new FeatureVector($features);

    foreach ($detectors as $detector) {
        foreach ($detector->process($vector) as $finding) {
            // handle finding
        }
    }
}
```

Detectors
---------

[](#detectors)

DetectorDetects`TrendDetector`Sustained upward/downward trends`NelsonRulesDetector`Statistical process control violations (8 Nelson rules)`EWMADetector`Subtle process shifts via exponentially weighted moving average`CUSUMDetector`Small persistent shifts via cumulative sums`DriftDetector`Long-term baseline movement`SpikeDetector`Isolated abnormal samples`StepDetector`Sudden permanent level changes`NoiseDetector`Signal instability / failing probes`ForecastResidualDetector`Deviations from linear forecast`SensorHealthDetector`Sample gaps, flatlines, stuck sensorsArchitecture
------------

[](#architecture)

```
Raw Measurements
       |
FeatureCalculator  (rolling stats, regression, EMA, control limits)
       |
  FeatureVector
       |
  Detectors  →  AnalyticalFinding[]

```

Each detector is stateless or maintains minimal internal state (rolling buffers, accumulators). Detectors declare which features they need via `requires()`.

See [architecture/detectors.md](architecture/detectors.md) for the full pipeline design (behaviour, process, and diagnosis layers).

Testing
-------

[](#testing)

```
composer install
vendor/bin/phpunit
```

###  Health Score

23

—

LowBetter than 25% of packages

Maintenance65

Regular maintenance activity

Popularity7

Limited adoption so far

Community6

Small or concentrated contributor base

Maturity11

Early-stage or recently created project

 Bus Factor1

Top contributor holds 100% of commits — single point of failure

How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window.

**Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores.

**Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement.

**Maturity (30%)** — Project age, version count, PHP version support, and release stability.

### Community

Maintainers

![](https://avatars.githubusercontent.com/u/9331242?v=4)[James Lucas](/maintainers/lucasnetau)[@lucasnetau](https://github.com/lucasnetau)

---

Top Contributors

[![lucasnetau](https://avatars.githubusercontent.com/u/9331242?v=4)](https://github.com/lucasnetau "lucasnetau (6 commits)")

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```

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