Real-time and non-intrusive on-site diagnosis for commissioning wireless sensor and actuator networks in building automation

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Abstract

Wireless Sensor and Actuator Networks (WSANs) are widely used in Building Automation Systems (BASs). The field commissioning of WSANs is generally considered to be time consuming and labor intensive. To increase the efficiency of commissioning process, an on-site diagnosis is extremely important. In this paper, a novel real-time and non-intrusive on-site diagnosis (OSD) for WSANs in BASs is proposed. It implements Out-of-Band Bluetooth Low Energy (BLE) to transmit diagnosis information without interference on the normal traffic of the BA field network, which has been validated through experiments. By proper utilization of our OSD system, installers can obtain a comprehensive knowledge of the network, which make commissioning much more efficient and cost effective.

Introduction

Building Automation Systems (BASs) have been widely applied to a variety of commercial buildings [1], [2], [3]. They employ sensors and actuators dispersed in buildings to control the heating, ventilation, air conditioning, door access, fire alarming, etc. The application of wireless communication and smart object technology makes the deployment of BASs more flexible and cost effective [4]. Indeed, Wireless Building Automation (WiBA) systems ease the installation and updating process when changes in the building occur. IETF IoT [5] is a promising standard for WiBA since it offers native support of IP (NIP), which enables the direct communication between IP devices locally or via IP network [6]. Thus, the interoperability, scalability and flexibility of WiBA are guaranteed. Field commissioning is an important part of the installation and maintenance of BAS [7]. However, it is time consuming and costly in WiBA systems [8]. Because of the instability and time-varying characteristic of wireless link, it always happens that some devices fail to join the network at first or lose the connection afterwards due to the poor link quality [9]. In that case, it is extremely difficult for the installers to do the troubleshooting. If network connectivity and performance analysis of the WiBA system can be obtained and displayed to installers in a visual way, enabling the installers to have a comprehensive knowledge of the WiBA network, the commissioning will be more efficient and convenient. This would greatly save the manpower and the material resources so that the expense for commissioning is decreased. To get these kinds of information, on-site diagnosis support is crucial. In practical test, BA devices generate several information from the implementation of each layer's protocol. Unfortunately, IETF IoT does not make each layer's information available for users [4]. Thus, an additional diagnosis tool is an essential complement on the existing IP-based WiBA Systems. It is also worth noting that even though on-site diagnosis is demanded, this mechanism cannot affect normal operation and traffic of the system [10].

There are some tools designed for traditional WSANs [11]. Clairvoyant [12], which is a node state tool, uses on-node components to output node information for diagnosing. However, it doesn't provide platform diversity and generally leads to high node resource consumption, which affects the normal operation of the system [13]. In [14], a novel on-site Hand-Held Device based (HHD-based) toolset is proposed to carry out the deployment and commissioning of WSN-based systems. This toolset obtains the sensor platform parameters by the communication of the HHD with the deployed node. However, the sensor node should have a ‘plug-in’ integrated to realize this function, which needs extra devices and may also be platform-specific. Moreover, the two tools discussed before are not designed for IP-based WSANs. There are few proposals focused on-site diagnosis for IP-based WSANs, such as the one defined by the 6LoWPAN IETF standard, which provides support for Internet Protocol version 6 for low-power WSANs used in IoT applications [15]. One diagnosis tool especially for 6LoWPAN is Foren6, which is a traffic-based diagnosis tool [16]. It relies on single or multiple sniffers to capture 6LoWPAN traffic and display the network state on a GUI, thus providing high platform diversity and having no impact on the monitoring network. However, its diagnosis ability is constrained by the coverage of the sniffer and the diagnosis result is generally off-line, which cannot meet the requirement of real-time on-site diagnosis.

In this paper, we propose a novel on-site diagnosis (OSD) method for the field commissioning of WSANs in BASs. The main contributions of this paper are: (i) a real-time diagnosis tool independent of extra sniffers is proposed so that the network state is dynamically updated to installers; (ii) no extra sub-devices need to be added to the BA devices; (iii) Bluetooth

Low Energy (BLE) transmission is implemented for OSD system [17]. Diagnosis data are transmitted as Bluetooth beacons, avoiding interfering with the normal traffic of BAS. It is also proved that BLE is fast enough for real-time OSD; (iv) the diagnosis tool is ready-to-use and available for installers who have no relevant experience of installation and commissioning. The required developer effort is relatively low.

Section snippets

Overview

Fig. 1 illustrates the system architecture for real-time OSD system in BAS. It is composed of four main parts: Building Automation Device (BA Device) with Out-of-Band OSD, OSD Middleware, OSD Server and Installer UI. BA Devices with Out-of-Band OSD can operate on either IETF mode or BLE mode. Most of the time, they are under IETF mode, responsible for forming the IETF field network and acting as sensors and actuators of BAS. During the idle periods of the IETF mode, they will switch to BLE mode

Implementation

An implementation for the OSD system is displayed in Fig. 2, emphasizing the transition mechanism between IETF mode and BLE mode of the BA devices. More details will be given in the following.

Experimental results

The experimental evaluation of the real-time OSD system for BA is provided in this section, including test setup, beacon specification and web UI description. To discover the possible influence of the period interval for Bluetooth beacon transmission, a test for measuring the Round Trip Time (RTT) of 2-hop devices with different beacon transmission intervals is carried out.

Conclusion

Since the field commissioning of native-IP WiBA system is time-consuming and expensive, an efficient on-site diagnosis is necessary to support the commissioning. In this paper, we propose a novel real-time and non-intrusive on-site diagnosis for WSANs in BA systems. The complete implementation of the OSD system is presented, including the Bluetooth beacons, the Android App and the web UI. Out-of-Band BLE is implemented to transmit the diagnosis information in order to avoid interference of the

References (20)

  • Z. Pang

    Technologies and Architecture of the Internet-of-Things (IoT) for Health and Well-being

    (2013)
  • F. Osterlind et al.

    Integrating building automation systems and wireless sensor networks

  • W. Kastner et al.

    Communication systems for building automation and control

    Proc. IEEE

    (2005)
  • C. Reinisch et al.

    Wireless technologies in home and building automation

  • Z. Sheng et al.

    A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities

    IEEE Wirel. Commun.

    (2013)
  • W. Granzer et al.

    Securing IP backbones in building automation networks

  • D.E. Claridge et al.

    Is commissioning once enough?

    Energy Eng.

    (2004)
  • V.C. Gungor et al.

    Industrial wireless sensor networks: challenges, design principles, and technical approaches

    IEEE Trans. Indust. Electron.

    (2009)
  • A. Willig et al.

    Wireless technology in industrial networks

    Proc. IEEE

    (2005)
  • Y. Liu et al.

    Passive diagnosis for wireless sensor networks

    IEEE/ACM Trans. Netw.

    (2010)
There are more references available in the full text version of this article.

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