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ixc2025:lappeenranta:team_3:start [2025/05/21 15:03] – [4. Finalized Idea, description & Functions] ericrodeixc2025: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
Line 57: Line 57:
  
 - 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 ====+ 
 +==== 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. 
 + 
 +**1. Prevent Phone Usage** 
 +Effects: 
 + 
 +Improved sleep hygiene (Individual) 
 + 
 +Reduction of digital addiction (Social) 
 + 
 +Potential resistance from users (Individual - Negative) 
 + 
 +Actions: 
 + 
 +Gradual enforcement; use messages before activating warning sounds. 
 + 
 +Provide override options for emergencies. 
 + 
 +**2. Coffee-Drinking Habit Alert** 
 +Effects: 
 + 
 +Reduced caffeine-related sleep disturbances (Individual) 
 + 
 +Increased user awareness of consumption habits (Individual) 
 + 
 +Potential frustration or non-compliance (Social - Negative) 
 + 
 +Actions: 
 + 
 +Provide a bypass with confirmation. 
 + 
 +Collect data to optimize timing alerts over time. 
 + 
 +**3. Turn Off Unnecessary Appliances** 
 +Effects: 
 + 
 +Energy conservation (Environmental) 
 + 
 +Safety improvement (Social) 
 + 
 +Reduced electricity costs (Economic) 
 + 
 +Actions: 
 + 
 +Smart schedule optimization based on actual usage patterns. 
 + 
 +**4. Sleeping Time Reminder** 
 +Effects: 
 + 
 +Encourages regular sleep patterns (Individual) 
 + 
 +Reduces screen time exposure at night (Social/Individual) 
 + 
 +Potentially intrusive if not customizable (Negative) 
 + 
 +Actions: 
 + 
 +Make reminders adaptive and user-configurable. 
 + 
 +**5. Automatic Exposure to Natural Light** 
 +Effects: 
 + 
 +Aligns circadian rhythm with daylight (Individual) 
 + 
 +Enhances mood and productivity in the morning (Social) 
 + 
 +Reduces need for artificial lighting (Environmental) 
 + 
 +Actions: 
 + 
 +Adjust based on sunrise time dynamically. 
 + 
 +**6. Sleeping Environment Optimization** 
 +Effects: 
 + 
 +Improved sleep quality through ideal room conditions (Individual) 
 + 
 +Energy-efficient ventilation and fan use (Environmental/Economic) 
 + 
 +Actions: 
 + 
 +Allow customization of temperature and humidity thresholds. 
 + 
 +**7. Noise and Activity Detection at Night** 
 +Effects: 
 + 
 +Enhances feeling of safety and calm (Social/Individual) 
 + 
 +May cause disturbance if false positive (Technical/Negative) 
 + 
 +Actions: 
 + 
 +Use multiple sensors to validate activity before reacting. 
 + 
 +__LIST OF EFFECTS__ 
 + 
 +**SOCIAL DIMENSION** 
 + 
 +High likelihood - High impact 
 + 
 +Positive: 
 + 
 +Enforced digital detox improves quality of interactions. 
 + 
 +Safer environment by shutting off appliances. 
 + 
 +Negative: 
 + 
 +Resistance to imposed behaviors (e.g., phone removal, coffee restrictions). 
 + 
 +**INDIVIDUAL DIMENSION** 
 +High likelihood - High impact 
 + 
 +Positive: 
 + 
 +Better sleep from controlled environment and reduced caffeine. 
 + 
 +More consistent circadian rhythms. 
 + 
 +Negative: 
 + 
 +Discomfort due to automation override (e.g., blocked coffee brewing). 
 + 
 +**ENVIRONMENTAL DIMENSION** 
 +High likelihood - High impact 
 + 
 +Positive: 
 + 
 +Lower electricity use due to appliance management. 
 + 
 +Natural light use reduces carbon footprint. 
 + 
 +**ECONOMIC DIMENSION** 
 +High likelihood - Low impact 
 + 
 +Positive: 
 + 
 +Marginal cost savings from reduced energy use. 
 + 
 +Fewer replacements due to appliance overuse. 
 + 
 +**TECHNICAL DIMENSION** 
 +Low likelihood - High impact 
 + 
 +Negative: 
 + 
 +Risk of system failure or false positives causing sleep disruption. 
 + 
 +Hardware dependency (sensors, window motors) increases maintenance need. 
  
  
 ==== 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