🗣️ How the Ovilus Actually Works
The Ovilus is marketed as a device that "converts environmental energy into words" for spirit communication. But what's really happening inside?
The Algorithm (Simplified)
// Commercial Ovilus Algorithm (our best reverse-engineering)
1. Read environmental sensors:
- Temperature: 22.5°C
- Humidity: 45%
- Pressure: 1013 hPa
- Magnetic field: 512 (analog reading)
2. Combine into a hash value:
hash = (temp * 1000 + humidity * 100 + pressure + mag_field)
hash = (22500 + 4500 + 1013 + 512) = 28,525
3. Map hash to word index:
word_index = hash % WORD_COUNT
word_index = 28,525 % 512 = 397
4. Look up word in database:
word = dictionary[397] // e.g., "DANGER"
5. Display and/or speak the word
The Math: How Many Unique Combinations?
Sensor Resolution:
• Temperature (BME280): 0.01°C precision
Range: 15°C to 35°C = 2,000 unique values
• Humidity (BME280): 0.01% precision
Range: 0% to 100% = 10,000 unique values
• Pressure (BME280): 0.01 hPa precision
Range: 950 to 1050 hPa = 10,000 unique values
• Magnetic (Hall sensor): 12-bit ADC
Range: 0 to 4095 = 4,096 unique values
Total Possible Combinations:
2,000 × 10,000 × 10,000 × 4,096 = 819,200,000,000,000
That's 819 TRILLION unique environmental states!
⚠️ The Psychology of Small Word Databases
Why Commercial Devices Use Only 512-2048 Words
It's not a technical limitation - it's psychological manipulation.
Commercial Ovilus devices deliberately use small word databases to create artificial repetition:
- 512 words = 1.6 trillion sensor combinations per word
- 2,048 words = 400 billion sensor combinations per word
- 10,000 words = 82 billion sensor combinations per word
What this means in practice:
With a 512-word database, if the room gets slightly warmer (22.5°C → 22.6°C), the device might still output the same word because billions of different sensor states map to the same word.
Why they do this:
- ✅ Pattern recognition bias: "It said DANGER three times - the spirit is warning us!"
- ✅ Confirmation bias: Repeated words feel more significant than random variety
- ✅ Illusion of communication: "It's responding to my questions with the same word!"
- ✅ Proprietary mystique: Small database = "carefully curated spirit vocabulary"
The truth: More words = better statistical distribution = more variety = less "spooky" repetition = less interesting for paranormal TV shows.
Word Database Size Comparison
| Word Count |
Sensor States Per Word |
Behavior |
Use Case |
| 100 words |
8.2 trillion |
Extremely repetitive - same words over and over |
Beginner demo/testing |
| 512 words |
1.6 trillion |
High repetition - "classic" Ovilus behavior |
Mimics commercial Ovilus I/II |
| 2,048 words |
400 billion |
Moderate repetition - feels "responsive" |
Mimics commercial Ovilus III/IV |
| 10,000 words |
82 billion |
Low repetition - good statistical distribution |
Scientific investigation, better variety |
| 50,000+ words |
16 billion |
Minimal repetition - nearly unique per state |
Maximum entropy, data analysis |
OpenParanormal Advantage: You Choose!
Our open-source firmware lets you configure word database size:
- Classic Mode (512 words): Hardcoded in firmware - mimics commercial behavior for pattern-seeking investigators
- Extended Mode (2,048 words): Hardcoded in firmware - balanced repetition vs. variety
- Dictionary Mode (10,000+ words): Load from microSD card - scientific investigation with proper statistical distribution
- Custom Mode: Create your own word lists - investigation-specific vocabularies (e.g., historical names, location-specific terms)
Why this matters: Transparency lets you understand bias in your data. If you know the device repeats words due to algorithm design (not spirits), you can make informed interpretations.
📡 EMF Meters: What They Actually Detect
EMF (Electromagnetic Field) meters measure magnetic fields in the environment. Commercial paranormal EMF meters work identically to electrician's EMF meters - the difference is just marketing.
What Creates EMF in Your Environment
- AC Power Lines: 60Hz (US) or 50Hz (Europe) magnetic fields from household wiring
- Electrical Devices: Transformers, motors, chargers, appliances
- Radio Transmitters: Cell towers, WiFi routers, radio stations
- Natural Sources: Earth's magnetic field (~0.5 mG), lightning, solar activity
- Faulty Wiring: Creates higher-than-normal EMF spikes
The "EMF = Ghosts" Hypothesis
Popular theory: Spirits manipulate electromagnetic fields to manifest or communicate.
Scientific reality: No controlled experiments have demonstrated paranormal EMF manipulation. All documented EMF spikes have prosaic explanations:
- Wiring in walls (especially old buildings)
- Electrical panel boxes
- Appliances turning on/off automatically
- Cell phone signals (investigator's own phone!)
- Fluorescent lights (even when "off" can leak EMF)
Our approach: Log ALL EMF data with timestamps, correlate with environmental factors, look for patterns - not cherry-pick "anomalies."
Commercial K2 Meter vs. DIY EMF Meter
✅ OpenParanormal EMF Meter
- Logs data to SD card with timestamps
- Graphical display shows trends
- Calibrated readings in milligauss (mG)
- Costs $15 to build
- Open-source = understand the algorithm
⚠️ Commercial K2 Meter
- No data logging - just LEDs
- No calibration - arbitrary LED thresholds
- Costs $50-70
- Black box design - can't verify accuracy
- Optimized for dramatic TV reactions
📻 Spirit Box: Radio Static or Communication?
A Spirit Box rapidly scans AM/FM radio frequencies, creating white noise from fragments of radio stations. The theory: spirits manipulate this radio static to form words.
How It Works
Spirit Box Algorithm:
1. Tune radio to starting frequency (e.g., 87.5 MHz FM)
2. Wait X milliseconds (sweep speed, e.g., 50ms)
3. Increment frequency by 0.1 MHz
4. Repeat from 87.5 to 108.0 MHz
5. Loop forever
What you hear:
• Brief fragments of radio stations (music, talk, ads)
• Static (white noise between stations)
• Occasional clear words (from actual broadcasts)
• "Pareidolia effect" - brain pattern-matches noise into words
The Psychology: Audio Pareidolia
Pareidolia is the tendency to perceive meaningful patterns in random stimuli. With audio:
- Your brain is designed to extract speech from noise (evolutionary advantage)
- Rapid radio scanning creates random audio fragments
- Your brain fills in gaps, creating "words" from static
- Confirmation bias: you hear what you expect/want to hear
Test: Use a Spirit Box in different languages/countries. "Spirits" will speak the local language of radio broadcasts - not Latin or ancient languages.
OpenParanormal Advantage: Recording & Analysis
Our Spirit Box can record sessions to SD card, allowing:
- Playback at different speeds (slow down to analyze fragments)
- Spectral analysis (identify if "words" are from radio stations)
- Blind listening tests (remove investigator bias)
- Correlation with other sensor data (EMF spikes, temperature)
💡 Novel Device Ideas: Inventing New Tools
Beyond copying commercial equipment, OpenParanormal can pioneer new investigation methods based on sensor technology and data science:
1. Environmental Change Correlator
Concept: Instead of measuring individual sensors, detect simultaneous changes across multiple sensors.
Hardware:
- BME280 (temp/humidity/pressure)
- EMF sensor (magnetic field)
- Microphone (audio level)
- PIR motion sensor
- All logged with microsecond timestamps
Algorithm:
// Detect correlated anomalies
if (temp_delta > threshold AND
emf_delta > threshold AND
audio_spike detected AND
all within 100ms window) {
FLAG AS ANOMALY
Log all sensor values + timestamp
}
Why this is better: Filters out individual false positives. Correlated multi-sensor events are statistically rarer and harder to explain via environmental factors.
2. Entropy Analyzer
Concept: Measure "randomness" in environmental data vs. expected baseline.
Theory: If paranormal phenomena exist, they might introduce non-random patterns (or extra randomness) into sensor data.
Hardware:
- High-speed ADC sampling ambient EM noise
- Temperature sensor array (multiple points)
- Accelerometer (vibration/movement)
Algorithm:
// Statistical entropy calculation
1. Establish baseline entropy over 60 seconds
2. Continuously measure entropy in rolling 5-second windows
3. Calculate z-score (how many standard deviations from baseline)
4. Alert on significant deviations (z > 3.0 or z < -3.0)
5. Log all raw data for post-analysis
Scientific value: Quantifiable metric. Can be tested in controlled vs. "haunted" environments.
3. Infrasound Detector
Concept: Measure sound below human hearing range (< 20 Hz).
Why this matters:
- Infrasound (especially 18-19 Hz) can cause feelings of unease, dread, visual distortions
- Sources: HVAC systems, wind, traffic, geological activity
- Many "haunted" feelings may be infrasound exposure
Hardware:
- Low-frequency microphone or custom resonant chamber
- ESP32 with FFT analysis
- Display shows 0-20 Hz spectrum in real-time
Scientific value: Distinguish psychological effects (infrasound-induced) from potential paranormal phenomena.
4. Baseline Environment Mapper
Concept: Create a "normal" baseline map of a location before investigation.
Process:
- Mapping phase (daytime): Walk through location with device, logging EMF, temp, humidity, light levels every meter
- Analysis: Generate heatmap of "normal" readings
- Investigation phase (nighttime): Device alerts only when readings deviate significantly from baseline map
Hardware:
- GPS module or manual room selection
- Multi-sensor array (EMF, temp, humidity, light)
- MicroSD for storing baseline profiles
- Visual/audio alert when anomaly detected
Why this is revolutionary: Eliminates false positives from environmental factors (e.g., "high EMF" is just a wall outlet). Only true changes trigger alerts.
5. The "Control Device" - Placebo Detector
Concept: A fake device that looks identical to real equipment but generates random data.
Scientific purpose:
- Blind studies: Give investigators 2 devices (1 real, 1 fake), don't tell them which is which
- If both devices get "equal" paranormal hits → investigator bias confirmed
- If real device significantly outperforms fake → possible genuine signal
Hardware: Identical case to real EMF/Ovilus, but outputs random values
Ethical note: Only for controlled experiments, with informed consent afterward
🔬 Bringing Science to Paranormal Investigation
The Problem with Traditional Ghost Hunting
- Cherry-picking data: Only reporting "hits," ignoring misses
- Confirmation bias: Interpreting ambiguous data as supporting pre-existing beliefs
- Lack of controls: Not testing equipment in non-"haunted" locations
- Black-box equipment: Not understanding how devices work
- No data logging: Relying on memory and subjective interpretation
The OpenParanormal Scientific Approach
Core Principles
- Log everything: All sensor data, all the time, with timestamps
- Establish baselines: Measure "normal" conditions before claiming anomalies
- Use controls: Test equipment in known non-paranormal environments
- Understand your tools: Open-source = you know exactly how devices work
- Blind analysis: Have someone unfamiliar with the investigation review data
- Quantify uncertainty: Use statistics, not just "we felt something"
- Replicate findings: Anomalies should repeat under similar conditions
- Rule out mundane explanations first: Is it a draft? Faulty wiring? Radio interference?
Data Analysis Best Practices
Example Investigation Protocol:
Phase 1: BASELINE (1 hour minimum)
- Deploy all sensors in location
- Log all data continuously
- Calculate mean, standard deviation for each sensor
- Identify environmental patterns (HVAC cycles, traffic noise, etc.)
Phase 2: INVESTIGATION (2-4 hours)
- Continue logging all sensors
- Mark events manually (investigator notes, timestamps)
- Do NOT review data during investigation (avoid bias)
Phase 3: ANALYSIS (offline)
- Load all sensor logs into analysis software
- Flag readings > 2 standard deviations from baseline
- Correlate multi-sensor anomalies (within ±1 second)
- Compare "anomaly" frequency to control dataset
- Statistical significance: p < 0.05 to claim finding
Phase 4: REPLICATION
- Return to location at different time/date
- Repeat investigation with same equipment
- Compare datasets - do anomalies occur in same locations?
- Only report findings that replicate across sessions
Publishing Your Findings
OpenParanormal encourages investigators to share data openly:
- Raw data dumps: Upload sensor logs to public repositories (GitHub, OSF)
- Methodology transparency: Document equipment specs, calibration, analysis methods
- Negative results count: "We found nothing anomalous" is valuable data
- Peer review: Let other investigators analyze your data independently
🎯 The Mission: Elevate Paranormal Investigation
OpenParanormal exists to bring transparency, scientific rigor, and affordability to ghost hunting. We believe:
- Understanding = Better Investigation: Knowing how equipment works helps you interpret data correctly
- Science ≠ Skepticism: Scientific method doesn't assume paranormal phenomena don't exist - it provides tools to test hypotheses rigorously
- Open Source = Truth: Commercial black-box devices hide their flaws. Open-source reveals both capabilities and limitations
- Data > Feelings: Logged, timestamped data is more reliable than subjective experiences
- Innovation Through Sharing: When investigators share designs and data, the entire field advances
Build. Investigate. Share. Advance the science.