6.1.2.1 Food and water intake monitoring

A designed water and food dispenser monitors the patient and can provide him with the food he needs. The system ensures that the patient drinks enough water so as to prevent him from feeling thirsty.

#### 6.1.2.1.1 Food order process


#### 6.1.2.1.2 Food dispenser


#### 6.1.2.1.3 Reminder for family member

In case a family member is at home and wants to care for the patient, WaFoD sends an alert to the member.

In the case of ordering food, then food order process will run otherwise the food dispenser will run.

## 6.1.2.2 Medication intake monitoring

Similar to food intake, a drug dispenser is equipped with a high-resolution camera which logs the drug intake. A future extension will automatically perform anomaly detection on recorded films.

data. Patient-centered data are data provided by the patient through narratives, while patient-centric data are data collected using modern information technologies like (wireless) body area network (W-BAN) or (wireless) sensor networks (WSNs). Aging persons are often forgetful and thus provide mostly biased information when they are requested to report on their health conditions. Though in a smart home automation enabled healthcare solution for "aging well," collecting patientcentric data in an autonomous way is mandatory. In a previous study [35], various advantages of collecting patient-centric data were discussed. The healthcare personal gets a complete picture of the patient's health condition and can thus pose the

IoT-Enabled Health Monitoring and Assistive Systems for in Place Aging Dementia Patient…

Based on the requirement above, the proposed concept provides a patientcentric data collector in terms of sensors connected with the patient that fully collects any bio-signal as well as positions data and sends the data to a record system at the remote. A duplicated copy of the data is saved on the local server and serves as training data for a machine learning (ML) routing. Additionally, a set of networking capable video recorders are used to collect the patient's body expressions, behaviors, mimic, and any physical activities. These data are also used by the ML algorithm to predict patient's behaviors, expectations, and physiological needs (like

Sensors (in a body area network) connect the patient to an IoT-gateway that transfers the collected data, using the MQTT protocol, to the local server. We talk of edge-computing that happens at the edge. Collected data are processed and stored on the local server. Using the CoApp protocol, data are sent to the cloud. Treating care/nursing homes or medical doctor as well as patient's family members can access the data and can send data to the local server, which would use received data

For "food and water intake", a smart device is designed. This device combines microwaves and the fridge. The device called water and food dispenser (WaFoD) with networking ability is connected to the patient's smartphone and the local server, which in turn is connected to a remote server at the cloud that connects the home to the outside and can dispatch information and data in the whole network.

WaFoD is connected to the IoT gateway and can collect data, transfer data, and receive data from a remote unit (system or individual). Registered behaviors build the training data for a machine learning processor (ML) located on the local server,

WaFoD is designed to remind the patient to regularly drink water. It dispenses water or soft drinks. It can warm food and serve the food to the patient. The system logs each nutrition behavior and sends at the end of the day an activity journal, or in the case of emergency (that means the patient does not drink for a while or refuse to

The patient is provided with a touchscreen that displays TV programs and can

The entire system is designed following the Internet of things (IoT) paradigm: (i) data collection unit(s) and (ii) IoT-gateway place between the local server. The local server is a light copy of the remote server at the cloud, which can perform complex and

the master in the entire network. The ML processor predicts patient menus, proposes menus to the patient, and can order at the registered restaurant the selected menu. All proposed services to the patient are based on his behaviors and

WaFoD can learn from the individual's behaviors and preferences.

take food), it alerts the nursing home close to the patient's residence.

memory consuming computing activities; (iii) the IoT platform at the cloud.

display the pictures of menus proposed by WaFoD.

right diagnosis.

preferences.

97

thirst, hunger, going to the toilet, etc.).

DOI: http://dx.doi.org/10.5772/intechopen.86247

to regulate some connected devices.

6.1.3.1.2 Food and water intake and control

The medication intake is then logged. The logs are sent to the family member and the doctor.

### 6.1.2.3 Physical activities (in- and outdoor activities)

Special TV programs are displayed at certain times of the day to help the patient to train himself. The patient wears a body-area-networking (BAN) equipped with bio-sensors and accelerometer, which continually controls the position of the patient in order to detect if the patient is falling down or lying on the bed.

For dementia patients, no outdoor program is set.

#### 6.1.2.4 Room temperature monitoring

Temperature control is a well-achieved domain application in smart home automation. Existing devices and systems are added to the network.

#### 6.1.2.5 Noise and lighting control

This feature prevents any noise and controls the lighting.

#### 6.1.2.6 Window and door monitoring

Doors and windows are controlled and closed when too noisy.

#### 6.1.2.7 Reminder and assistance for indoor and outdoor

A smartphone-based application plays the role of a reminder and assistant. It follows the patient everywhere. Based on the patient calendar, this application can autonomously and automatically plan the whole day for the patient.

It can look for an appointment with the treating doctor for the next medical visit. The application is parametrizable.

#### 6.1.3 Concept and architectural view

This section presents the concept of the proposed systems and gives an overview of its architecture.

The system features (i) a data perception unit, (ii) water, food, and medication management unit, and (iii) outside and inside activities.

#### 6.1.3.1 Concept

#### 6.1.3.1.1 Data gathering

IoT-enabled patient-monitoring systems present many advantages for the patient and for treating care personnel. Patient-centric data are collected. Personalized care can be based on these data. Actually, healthcare professionals base their treatment on patient-centered data, which can be biased since they are subjective. Further diagnoses are therefore needed or performed to verify the patient-centered

#### IoT-Enabled Health Monitoring and Assistive Systems for in Place Aging Dementia Patient… DOI: http://dx.doi.org/10.5772/intechopen.86247

data. Patient-centered data are data provided by the patient through narratives, while patient-centric data are data collected using modern information technologies like (wireless) body area network (W-BAN) or (wireless) sensor networks (WSNs).

Aging persons are often forgetful and thus provide mostly biased information when they are requested to report on their health conditions. Though in a smart home automation enabled healthcare solution for "aging well," collecting patientcentric data in an autonomous way is mandatory. In a previous study [35], various advantages of collecting patient-centric data were discussed. The healthcare personal gets a complete picture of the patient's health condition and can thus pose the right diagnosis.

Based on the requirement above, the proposed concept provides a patientcentric data collector in terms of sensors connected with the patient that fully collects any bio-signal as well as positions data and sends the data to a record system at the remote. A duplicated copy of the data is saved on the local server and serves as training data for a machine learning (ML) routing. Additionally, a set of networking capable video recorders are used to collect the patient's body expressions, behaviors, mimic, and any physical activities. These data are also used by the ML algorithm to predict patient's behaviors, expectations, and physiological needs (like thirst, hunger, going to the toilet, etc.).

Sensors (in a body area network) connect the patient to an IoT-gateway that transfers the collected data, using the MQTT protocol, to the local server. We talk of edge-computing that happens at the edge. Collected data are processed and stored on the local server. Using the CoApp protocol, data are sent to the cloud. Treating care/nursing homes or medical doctor as well as patient's family members can access the data and can send data to the local server, which would use received data to regulate some connected devices.

#### 6.1.3.1.2 Food and water intake and control

For "food and water intake", a smart device is designed. This device combines microwaves and the fridge. The device called water and food dispenser (WaFoD) with networking ability is connected to the patient's smartphone and the local server, which in turn is connected to a remote server at the cloud that connects the home to the outside and can dispatch information and data in the whole network. WaFoD can learn from the individual's behaviors and preferences.

WaFoD is connected to the IoT gateway and can collect data, transfer data, and receive data from a remote unit (system or individual). Registered behaviors build the training data for a machine learning processor (ML) located on the local server, the master in the entire network. The ML processor predicts patient menus, proposes menus to the patient, and can order at the registered restaurant the selected menu. All proposed services to the patient are based on his behaviors and preferences.

WaFoD is designed to remind the patient to regularly drink water. It dispenses water or soft drinks. It can warm food and serve the food to the patient. The system logs each nutrition behavior and sends at the end of the day an activity journal, or in the case of emergency (that means the patient does not drink for a while or refuse to take food), it alerts the nursing home close to the patient's residence.

The patient is provided with a touchscreen that displays TV programs and can display the pictures of menus proposed by WaFoD.

The entire system is designed following the Internet of things (IoT) paradigm: (i) data collection unit(s) and (ii) IoT-gateway place between the local server. The local server is a light copy of the remote server at the cloud, which can perform complex and memory consuming computing activities; (iii) the IoT platform at the cloud.

6.1.2.2 Medication intake monitoring

anomaly detection on recorded films.

6.1.2.4 Room temperature monitoring

6.1.2.5 Noise and lighting control

6.1.2.6 Window and door monitoring

visit. The application is parametrizable.

6.1.3 Concept and architectural view

of its architecture.

6.1.3.1 Concept

96

6.1.3.1.1 Data gathering

6.1.2.3 Physical activities (in- and outdoor activities)

Internet of Things (IoT) for Automated and Smart Applications

For dementia patients, no outdoor program is set.

mation. Existing devices and systems are added to the network.

This feature prevents any noise and controls the lighting.

6.1.2.7 Reminder and assistance for indoor and outdoor

management unit, and (iii) outside and inside activities.

Doors and windows are controlled and closed when too noisy.

autonomously and automatically plan the whole day for the patient.

and the doctor.

Similar to food intake, a drug dispenser is equipped with a high-resolution camera which logs the drug intake. A future extension will automatically perform

The medication intake is then logged. The logs are sent to the family member

Special TV programs are displayed at certain times of the day to help the patient to train himself. The patient wears a body-area-networking (BAN) equipped with bio-sensors and accelerometer, which continually controls the position of the patient in order to detect if the patient is falling down or lying on the bed.

Temperature control is a well-achieved domain application in smart home auto-

A smartphone-based application plays the role of a reminder and assistant. It follows the patient everywhere. Based on the patient calendar, this application can

It can look for an appointment with the treating doctor for the next medical

This section presents the concept of the proposed systems and gives an overview

The system features (i) a data perception unit, (ii) water, food, and medication

IoT-enabled patient-monitoring systems present many advantages for the patient and for treating care personnel. Patient-centric data are collected. Personalized care can be based on these data. Actually, healthcare professionals base their treatment on patient-centered data, which can be biased since they are subjective. Further diagnoses are therefore needed or performed to verify the patient-centered
