Authors: Kim Lindholm ,Yeh-Liang Hsu (2016-05-14); Recommend:
Yeh-Liang Hsu (2016-05-14).
High level design of LAN
centric IoT network for supporting health and activity monitoring in the home
Background and Aim
Things (IoT) provides a great concept for automating and supporting health and
activity monitoring of older adults (Zhang and Zhang, 2011). IoT are mostly in cloud
centric structure, where devices connect to an external server in the “cloud”. Problem
with this kind of architecture is that if provider suddenly chooses to change
service agreement or turn off the server, end user would be left with useless
sensors and actuators. Also risks of data security are considerable when
sending data through Internet (Aazam, 2014). Moreover, privacy issues for
storing health data in the cloud server are often concerned by hospital,
nursing home and household users.
In this paper,
we propose using an edge server in the home environment for supporting activity
and health monitoring of older adults in daily life. Instead of storing user’s
private data in cloud servers far out of reach of end users, the data is stored
in the edge server in their own homes, so that users own the data, can access or
process the data when needed. The IoT edge server can also work as a Wi-Fi
router, building a “LAN centric IoT” network around it in the home environment.
structure, an edge server should provide the same services of a cloud server.
User interface can be built on its web service that can be accessed without
limitation from local area network and with specific set-up from wide area
network. It can connect devices using different protocols such as Wi-Fi and
Bluetooth, increasing the possibilities of IoT applications greatly. Capabilities
of data analysis and machine learning to detect patterns of activity and
abnormalities are also required.
Figure 1 shows
the high level design of LAN centric IoT network, where the edge server is at
the center point. Data is placed in external storage devices connected via USB
which is more portable and easily expanded. The edge server also works as a
Wi-Fi router at home. This way external access to the server is easier because
its IP address is always known from dynamic domain name system (DNS), and the
amount of devices in end users home can be reduced. To achieve external access
from outside of LAN, edge server supports dynamic DNS to update the server name
automatically in near real time.
connect to IoT devices via Bluetooth 4.1 and Wi-Fi. Edge server can dynamically
pass data information from Bluetooth device to Wi-Fi device and vice versa. Other
2.4GHz frequency protocols can be connected with an external hardware.
In our design,
Raspberry Pi 3 is used as an edge server. It has quad core ARM Cortex-A53,
1.2GHz CPU, 1GB LPDDR2 (900 MHz) RAM, 10/100 Ethernet, 2.4GHz 802.11n wireless
and Bluetooth 4.1 Classic and Bluetooth Low Energy. To achieve longer-range on Wi-Fi
network, the built in Wi-Fi is replaced by RTL8192CU USB Wi-Fi dongle with 5db
gain. Like previous models of Raspberry Pi, it has 4 USB ports to extend the
storage size and RAM. With these hardware specifications we can run MQTT
broker, Wi-Fi AP software, web server and data analysis calculations same time.
Figure 1. High level design for IoT Edge server
Results and Discussion
In this paper we
proposed a high level design of LAN centric IoT network using and edge server for
health and activity monitoring in the home environment. Its local data storage
saves private data only locally, giving the user full control and ownership over
it.The edge server also works as a Wi-Fi router for end users and a connection
point for IoT devices, as well as connecting Bluetooth devices with Wi-Fi
devices and vice versa.
On current state
of development of the edge server, we have already covered Wi-Fi router and
dynamic DNS and established all technologies for launching IoT edge server on an
embedded Linux computer Raspberry Pi 3. On future steps we will build similar
data analysis and machine learning services than cloud servers tend to provide and
start developing web user interface.
Gerontechnology Research Center (GRC), Yuan Ze University, we have designed
different types of sensors to measure activity and health of older adult, for example,
a battery powered PIR sensor to measure coarse location and activity inside of
the apartment and an electrical current sensor to detect the usage of
applications such as television. We are also looking into connecting some
exiting health monitoring appliances such as blood pressure and glucose
measurement to edge server. With wide range of sensors and powerful and robust
edge server we can develop and ease and secure health and activity monitoring
platform for older adults.
Zhang, X. M., & Zhang, N. (2011, May). An
open, secure and flexible platform based on internet of things and cloud
computing for ambient aiding living and telemedicine. In Computer and
Management (CAMAN), 2011 International Conference on (pp. 1-4). IEEE.
Aazam, M., Khan, I., Alsaffar, A. A., & Huh,
E. N. (2014, January). Cloud of Things: Integrating Internet of Things and
cloud computing and the issues involved. In Applied Sciences and
Technology (IBCAST), 2014 11th International Bhurban Conference
on (pp. 414-419). IEEE.