## 1 Introduction  
Power line networking devices were developed decades ago for automatic electricity-meter monitoring. Any electronic device connected to an electrical power line can use this technology for data communications without additional wiring. However, this use remains on the sidelines due to problems with quality of service, low data rates, range limitations, interoperability, and high cost. Recently, industries have provided remote reading for electricity meters via wireless connectivity, such as CDMA, GPRS, and PHS, using various radio spectra. These solutions are generally limited to peer-to-peer and one-level communication architectures [1]. When subjected to different user environments, they face various challenges. Therefore, we have developed an electricity meter monitoring network (EMMNet) based on heterogeneous smart sensor networks. According to the classification given by [PERSON] _et al_. a smart sensor includes certain functionalities such as processing, communication and integration [2]. The smart sensor is emerging as a promising technology in a large number of application domains. For instance, [PERSON] _et al_. [3] developed a smart sensor for real-time high-resolution frequency estimation in power systems. Their proposed smart sensor uses the chirp z-transform to compute the power spectrum and utilizes a commercially available current clamp, a Hall-effect sensor or a resistor as the primary sensor. [PERSON] _et al._[4] presented a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. [PERSON] _et al._[5] developed a fused smart-sensor in order to improve the online quantitative estimation of flank-wear area in CNC machine inserts, from the information provided by primary sensors such as the monitoring current output of a servoamplifier and an accelerometer. [PERSON] _et al._[6] developed a smart sensor system to acquire three types of signals involving vibration, current, and flux from induction motors. This system consisted of four modules: sensor, interface, server, and fault diagnosis module. The authors claimed that the smart sensor system can replace expensive traditional sensors for fault testing of induction motors. In most applications, a smart sensor node is expected to acquire some physical measurements, perform local processing and storage, and communicate within a short distance [7-9]. The ability to communicate not only allows information and control to be communicated across the network, but also enables nodes to cooperate in performing more complex tasks, such as statistical sampling, data aggregation, and system status monitoring [10]. Although sensor network platforms already exist, for electricity meter monitoring we have to design an entirely new system because a meter-monitoring scenario has specific requirements. First, wireless access is very challenging in urban environments, where electricity meters in tall buildings are often installed in a metal chest and separated by concrete walls. Most of the existing platforms can only provide very short-distance communication in this environment. We find that they cannot satisfy our requirements, through field measurement. Second, none of the existing platforms conform to the China National Standard for automatic electricity-meter monitoring. The radio frequency band is specifically designated to 470-510 MHz [11]. Finally, the nodes, which are called data collectors in the automatic electricity meter-reading field, need to be connected to electricity meters. Thus, we should consider safety factors in the node layout. In light of such needs, we present EMMNet, an integrated sensor environment for remote electricity meter monitoring. EMMNet is composed of data collectors, dataconcentrators, hand-held devices, a centralized server, and clients. The novelty of this work is the development of a smart sensor for real-time electricity meter monitoring.