An Overview of AI-Enabled Remote Smart- Home Monitoring System Using LoRa

An Overview of AI-Enabled Remote Smart- Home Monitoring System Using LoRa

Table of Contents





Abstract

Internet of Things (IoT) is a communication paradigm that connects devices and objects in order to harvest and process data produced by several edge devices [1]. It is predicting that with the current flow, the number of connected devices to the internet will be over 75 billion by 2025. It is predicted in [2] that the number of industrial IoT devices used for sensing, tracking, and controlling using low-power, wide area networks (LP-WAN)will ascent close to 0.5 billion by 2025. These massive connected IoT devices are expected to enforce enormous demand for channel capacity of the growing number of (LP-WAN) technologies[2], [3]. The LP-WAN technologies which are currently trading the markets are Long-range (LoRa), Sigfox, narrow-band IoT(NB-IoT), LTE-machine type communication (LTE-M), extended coverage global system for mobile communication (EC-GSM), random phase multiple access (RPMA), my-things (MIOTY), and DASH7. Wherein, LoRa, Sigfox, RPMA, MIOTY uses the unlicensed spectrum and others are based on cellular licensed spectrum. Fig. 1 depicts the list of LP-WAN technologies separated by the types of spectrum used. The respective downlink data rate and operating bandwidth are also mentioned in this figure. The unique characteristics of those LP-WAN technologies can be pointed as below:

  • Author Keywords

    • Low-power,
    • wide area network (LP-WAN),
    • internet of things (IoT),
    • long-range (LoRa),
    • smart home (SH),
    • artificial intelligence (AI)
  • IEEE Keywords

    • Intelligent sensors,
    • Sensor systems,
    • Artificial intelligence,
    • Servers,
    • Monitoring,
    • Cloud computing

Introduction

Internet of Things (IoT) is a communication paradigm that connects devices and objects in order to harvest and process data produced by several edge devices [1]. It is predicting that with the current flow, the number of connected devices to the internet will be over 75 billion by 2025. It is predicted in [2] that the number of industrial IoT devices used for sensing, tracking, and controlling using low-power, wide area networks (LP-WAN)will ascent close to 0.5 billion by 2025. These massive connected IoT devices are expected to enforce enormous demand for channel capacity of the growing number of (LP-WAN) technologies[2], [3]. The LP-WAN technologies which are currently trading the markets are Long-range (LoRa), Sigfox, narrow-band IoT(NB-IoT), LTE-machine type communication (LTE-M), extended coverage global system for mobile communication (EC-GSM), random phase multiple access (RPMA), my-things (MIOTY), and DASH7. Wherein, LoRa, Sigfox, RPMA, MIOTY uses the unlicensed spectrum and others are based on cellular licensed spectrum. Fig. 1 depicts the list of LP-WAN technologies separated by the types of spectrum used. The respective downlink data rate and operating bandwidth are also mentioned in this figure. The unique characteristics of those LP-WAN technologies can be pointed as below:

covers wide area providing long-distance communication,

  • devices consume very low power,
  • the low data rate,
  • low deployment costs.

These network protocols have already shown satisfactory performances in suitable sectors of diverse IoT applications [4]. The various sectors including but are not limited to transportation, healthcare, agriculture, and industry where it is expected to exploit the features of LP-WANtechnology. Remote patient monitoring, smart cities, smart grids, traffic lighting control, and metering systems are among the applications that require communications over a large geographical area based on cheap and low-power devices. Such devices can be deployed and moved around over a wide area with the support of LP-WAN [1], [2], [5], [6]. Specifically, remote smart home(SH) monitoring systems are achieving a great popularity in order to enhance the comfort and quality of life. These systems require smart IoT sensors network to sense, transmission and control the home environment, supplies, and instruments. The devices should consume very low power and the network provider have to cover the longer area to support remote monitoring. The existing short-range wireless technologies such as ZigBee [7], RFID[8], Wi-Fi [9], and Bluetooth low energy (BLE) [10] are not suitable for the applications where long-range communication is required even though they consume very low power. Moreover, conventional cellular networks consume a large amount of power for large coverage areas and higher manufacturing costs [11]. Therefore, to support remote control and monitoring of equipment among the other LP-WAN technologies LoRa is the most suitable in terms of both long-range and low power consumption as the channel throughput requirement is reasonably low for this system [12].

Conclusion

Wide area coverage, low power consumption, and inexpensive wireless connectivity are the main characteristics of LP-WAN systems. Lora is considered cheaper and longer battery life among other LP-WANtechnologies that can be best suitable for remote operations in an IoT-based SH presented in this paper. Lora integrated with AI learning models for IoT servers and clouds could serve intelligent tasks in a home environment. A dataflow design for the LoRa-based home monitoring using AI was presented. The advantages of using LoRa technology for home automation over other LPWA networks were also summarized in this work.

Acknowledgment

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-0-01396) supervised by the IITP (Institute for Information & communications Technology Promotion).

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FULL Paper PDF file:

An Overview ofAI-EnabledRemote Smart-Home Monitoring SystemUsing LoRa

Bibliography

author

M. Shahjalal, M. K. Hasan, M. M. Islam, M. M. Alam, M. F. Ahmed and Y. M. Jang,

Year

2020

Title

An Overview ofAI-EnabledRemote Smart-Home Monitoring SystemUsing LoRa

Publish in

2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Fukuoka, Japan, 2020, pp. 510-513,

Doi

10.1109/ICAIIC48513.2020.9065199.

PDF reference and original file: Click here

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Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.

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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.

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Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.