## 4 Use Case Study: [PERSON]'s Healthcare Monitoring
### Scenario Overview
```
1 defgenerate_sensor_data(num_readings):
2#Codetogeneraterandomsensordata
3 data=[]
4 for_inrange(num_readings):
5 heart_rate=random.randint(55,120)
6 blood_pressure_systolic=random.randint(85,140)
7 blood_pressure_diastolic=random.randint(55,90)
8 temperature=round(random.uniform(36.0,39.0),1)
9 data.append({
10'heart_rate':heart_rate,
11\"blood_pressure\":(blood_pressure_systolic,
11 blood_pressure_diastolic),
12\"temperature\":temperature
13}
14 returndata
```
Listing 1: Generate Sensor Data Function. Listing 2 shows the code for annotating sensor data. The heart rate readings are annotated as normal, elevated, or low, as shown in Figure 10.
```
1 defannotate_sensor_data(sensor_data):
2#Codetannotatesensordata
3 annotated_data=[]
4 forreadinginsensor_data:
5 heart_rate_status=\"Normal\"ifreading[\"heart_rate\"]<=100 else\"Elevated\"
6 blood_pressure_status=\"Normal\"if90<=reading[\"blood_pressure\"][0]<=120 else\"ElevatedorLow\"
7 temperature_status=\"Normal\"if36.5<=reading[\"temperature\"]<=37.5 else\"ElevatedorLow\"
8 annotated_data.append({
9'heart_rate':reading[\"heart_rate\"],
10'heart_rate_status\":heart_rate_status,
11\"blood_pressure\":reading[\"blood_pressure\"],
12\"blood_pressure_status\":blood_pressure_status,
13\"temperature\":reading[\"temperature\"],
14\"temperature_status\":temperature_status
15))
16 returnannotated_data
```
Listing 2: Annotate Sensor Data. Figure 11 depicts the distribution of heart rate readings generated by the above script, illustrating the type of data that SIM would handle and analyse in real-world applications. Simulating Data Encryption: The encryption process is a critical aspect of data security in SIM. It ensures that [PERSON]'s health data remains confidential and secure during transit and storage. The code shown in Listing 3 simulates the encryption of data using the SHA-256 hashing algorithm, reflecting the type of cryptographic operations that would be performed in the Data Security and Encryption Module. ```
1 defencrypt_data(data):
2#CodetosimulateencryptionusingSHA-256 hash
3 data_string=json.dumps(data).encode()
4 hash_object=hashlib.sha256(data_string)
5 returnhash_object.hexdigest()
```
Listing 3: Encryption using SHA-256. Simulating Smart Contract Execution: After securing the data, SIM interacts with the Blockchain Component to ensure the integrity and traceability of health data. The following snippet shown in Listing 4 simulates the execution of a smart contract within a blockchain network, an operation that would handle tasks such as verifying health data transactions or alerting healthcare providers in response to specific conditions detected in the data. ```
1 defexecute_smart_contract(encrypted_data):
2#Codetosimulatesmartcontractecution
3 if'a'inencrypted_data:#Placeholdercondition
4 print(\"SmartContract:Alertsenttohealthcareprovider.\")
5 else:
6 print(\"SmartContract:Noactioneeded.\")
```
Listing 4: Smart Contract Function. These simulations represent how SIM's Data Security and Encryption Module and Blockchain Component work together to maintain the security, integrity, and utility of health data. By encrypting the data and utilising smart contracts for data management, SIM ensures that health data like [PERSON]'s are handled securely and efficiently, facilitating trustworthy and responsive health monitoring and care. These operations, while simplified in the proof of concept, illustrate the potential of SIM to provide a robust framework for health data security and management in real-world applications. ### Simulating Third-Party Interactions

Within the comprehensive SIM framework, third-party interactions are facilitated by the Service Integration and Composition Module, Semantic Visualisation Component, and AI Feedback and Analysis Module. These modules ensure that the system not only captures and processes data efficiently but also interacts seamlessly with healthcare providers and patients. Here, we simulate potential interactions to demonstrate SIM's versatility and user-centric design.