## 4 Content Analysis and Data Mining
### Group 3: Energy Management and Artificial Intelligence
#### 4.3.3 Care Systems
Experiments are performed to assess the function of the proposed IHCAM-PUSH with different kinds of classifiers. The results showed that this model is successful, effective, fast, accurate, with a minimal fault in real-time big data acquisition and analysis, patient monitoring, and emergency cases (high blood pressure, irregular heartbeat). The findings of the experiment showed that applying sampling techniques alongside Spark enhances the accuracy of a classification and reduces overall error rate, especially for minority (emergency) classes. The best classifiers are decision tree (J48), random forest (RF), ripper classifier (JRip), and naive Bayes' (NB), respectively, that allow the best success rates in IHCAM-PUSH. Based on the experiment, the best sampling techniques are class balancer (CB) and synthetic minority over-sampling technique (SMOTE). Focusing on the operation of this framework for other diseases and further context modes are suggested for future study. [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] [53] developed a laboratory voice user interface (VUI) to integrate laboratory devices into an IoT environment in order to control them and read out their specific data. The system is equipped with photometer, VA-enabled device, cloud services (voice model and voice server, skill host, device shadow), local services (device server), laboratory devices, natural language processing (NLP) algorithms (to process speech inquiries and create speech output), and visual programming tool Node-RED 0.15.2 (for the integration of devices to IoT). Giving speech command by an operator, recognizing and recording speech by VA-enabled device, processing speech by cloud voice service, converting changes in the cloud service to commands by local services and device server, and reacting to the commands by lab devices are different stages of the system. To verify the system, some examples of speech commands for device interaction are performed, and the mean recognition accuracy of all performed phrases that lead to the same action is assessed. Analysis of the speech examples showed that the standard setting of this system proves a high mean accuracy (\(95\%\pm 3.62\)) of voice identification. This solution makes a hands-free device control and will be an assistant to physically impaired or low vision users. Security solutions that reflect common privacy rules are suggested to be worked on for future study. [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] [54] suggested a general platform, which combines complementary data from sensors. The platform monitors health conditions and consists of (1) Environmental sensors, all of which make a Zigbee or 6 LoWPAN-based wireless sensor networks, video sensors (RGB-D), which are connected to the Internet, and Bluetooth wearable sensors (which are low energy and have dual-accelerometers) connected to smartphone or tablet that are connected to a cellular network, (2) A home gateway, and (3) A data hub, environmental sensors collect the data of humidity, temperature, quality of air, level of noise, luminosity, occupancy, door information, and energy consumption accurately. Video sensors are RGB-D devices and are placed in different areas of the home. These sensors are supposed to gather the modulation or inflection of the voice of the residents, the residents' manner of walking, and their 3D pathway. Wearable sensors work based on dual-operation mode and make 50-Hz accelerator measurements in addition to localization services. Three sensing technologies are integrated to build the proposed platform, and the system works based on the following steps: Firstly, sensors (environmental sensors, video sensors, and wearable sensors) gather all the necessary data about the residents. Secondly, a gateway collects the data gathered from all sensor groups, secures the collected data in terms of privacy, and keeps the time synchronization.