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ixc2025:lappeenranta:team_3:start [2025/05/22 10:33] – [6. SUSAF Analysis] victor1207ixc2025:lappeenranta:team_3:start [2025/05/22 14:01] (current) – [8. Final Day Presentation Slides] ntd432
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 ==== 4. Finalized Idea, description & Functions ==== ==== 4. Finalized Idea, description & Functions ====
  
-Proposed main features, sorted by priority:+Proposed main features (Use Cases), sorted by priority:
   * Prevent phone usage   * Prevent phone usage
   * Coffee-drinking habit alert   * Coffee-drinking habit alert
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 - Automatically adjust the sleeping schedule of user by having them pushing the button when they wake up - Automatically adjust the sleeping schedule of user by having them pushing the button when they wake up
 +
 +==== 6. SusAF Analysis ====
 The Smart Sleep Assistant has 7 main features based on the research using SusAF. Possible effects found are presented for these features considering social, individual, environmental, economic and technical dimensions. A few possible actions were identified and are presented at the end of each feature. The Smart Sleep Assistant has 7 main features based on the research using SusAF. Possible effects found are presented for these features considering social, individual, environmental, economic and technical dimensions. A few possible actions were identified and are presented at the end of each feature.
  
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 Allow customization of temperature and humidity thresholds. Allow customization of temperature and humidity thresholds.
-** + 
-7. Noise and Activity Detection at Night**+**7. Noise and Activity Detection at Night**
 Effects: Effects:
  
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 ==== 7. Behavioral Change Analysis ==== ==== 7. Behavioral Change Analysis ====
 +| **Feature**                           | **Intended Behaviour Change**     | **Data to Track**                                 | **Device/Input Source**                         |
 +| **Prevent phone usage**               | Reduce phone usage before bed     | Phone presence on RFID; screen time after bedtime | RFID sensor, phone screen-time tracking         |
 +| **Coffee-drinking habit alert**       | Reduce caffeine intake in evening | Time of coffee button press                       | Button input with timestamp                     |
 +| **Turn off unnecessary appliances**   | Reduce distractions, energy use   | Appliance state after bedtime                     | Smart switches, time logs                       |
 +| **Sleeping time reminder**            | Encourage regular bedtime         | Adherence to bedtime schedule                     | System clock, user activity (PIR, phone use)    |
 +| **Natural light exposure in morning** | Align circadian rhythm            | Wake-up time consistency                          | Time of PIR activity or wearable wake detection |
 +| **Sleep environment optimization**    | Improve sleep quality             | Temp/humidity levels, fan/window state            | DHT sensor, actuator logs                       |
 +| **Noise & activity detection**        | Detect restlessness               | Motion events at night                            | PIR sensor                                      |
 +| **Self-reported sleep quality**       | Track subjective improvements     | Daily score (1–10 scale)                          | Manual user input on screen or app              |
  
  
-==== 8. Final Day Presentation Slides ====+| **Metric**                        | **How to Measure**                 | **Expected Change**         | 
 +| **Average bedtime**               | Time of last motion/phone use      | Earlier and more consistent | 
 +| **Wake-up time**                  | First PIR movement or wearable log | More consistent, earlier    | 
 +| **Phone usage after bedtime**     | Screen time log, RFID absence      | Decrease over time          | 
 +| **Coffee intake after 5 PM**      | Button press logs                  | Fewer presses after 5 PM    | 
 +| **Room conditions**               | Temp/humidity logs                 | More time in optimal range  | 
 +| **Nighttime disturbances**        | PIR sensor logs                    | Fewer movements at night    | 
 +| **Sleep score**                   | User self-report & wearable data   | Higher over time            | 
 +| **Sleep stages (REM/deep/light)** | Wearable logs (e.g., Oura)         | Higher % of deep/REM sleep  |
  
 +**Data Collection & Tools**
 +Sensors and Devices:
 +  * RFID sensor – Phone detection
 +  * PIR motion sensor – Movement before and during sleep
 +  * Button input – Coffee habit monitoring
 +  * Temperature & Humidity sensor (DHT11/DHT22) – Room environment
 +  * Smart appliances – Logs of on/off state
 +  * LCD Screen or App UI – Sleep reminders, feedback, manual input
 +  * Wearables (Oura Ring, Fitbit, etc.) – Sleep stage and heart rate data
  
-==== 9. Final Code ====+Storage: 
 +  * SD card or cloud logging (e.g., Firebase, Google Sheets) 
 +  * Time-stamped logs for sensor data 
 +  * Secure, anonymized user logs
  
 +**A. Quantitative Analysis:**
 +Track changes week-over-week or month-over-month
 +
 +Key comparisons:
 +  * Average bedtime before/after intervention
 +  * Caffeine intake frequency at night
 +  * Sleep duration and stage improvement
 +  * Night disturbances (motion events) reduced
 +  * Use graphs: sleep score trends, usage heatmaps, condition logs
 +
 +**B. Qualitative Analysis:**
 +  * Weekly reflections: user rates sleep quality & experience
 +  * Note perceived stress, restfulness, energy levels
 +  * Interview or survey users to understand comfort, usability
 +==== 8. Final Day Presentation Slides ====
 +
 +{{ :ixc2025:lappeenranta:team_3:smart-sleep-assistant-enhancing-sleep-and-efficiency.pptx |}}
 +==== 9. Final Code ====
  
 +https://github.com/ntd432/ssa