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4. Data Flow & Privacy Safeguards

| Step | Data Type | Privacy Mechanism | |------|-----------|-------------------| | Sensor Capture | Raw counts, flow, temperature | No PII | | Camera Capture | Low‑res grayscale frames | Edge‑level blur & skeletonization; no faces stored | | Transmission | Encrypted MQTT (TLS 1.3) | Mutual TLS authentication | | Storage | Time‑series in Cloud DB | Data retention policy (max 90 days for raw; aggregated for longer) | | Analytics | Model inputs only | Differential privacy for aggregate reporting | | User Feedback | Text via WhatsApp/Google Form | Consent‑based, GDPR‑compliant storage | The search term refers to an adult-oriented video

Conclusion

Recap the potential benefits of integrating ML into public toilet management and design.
Encourage stakeholders to consider the integration of smart technologies in public facilities for a better public experience.

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Technology can play a significant role in maintaining public toilets. For example:

# ------------------------------------------------- # 1. Load historic door‑counter data (5‑min intervals) # ------------------------------------------------- df = pd.read_csv('toilet_occupancy.csv', parse_dates=['timestamp']) df.set_index('timestamp', inplace=True)

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Best Practices for Ensuring Cleanliness and Hygiene