## 1 Introduction  
Today, we assist the great emergence of wireless sensor networks. These kinds of networks are self-organized and consist in general of a large amount of autonomous sensor nodes with low resources transmitting sensed data to the base stations [1]. A sensor network can be easily deployed over large areas, but once deployed, it can be very difficult or even impossible to access. That is why most of these networks intend to optimize the use of the limited energy contained in each node. Energy optimization can be obtained by an efficient hardware architecture, efficient data routing and aggregation, energy harvesting and many other ways. Many application fields tend to take advantage of the technology of wireless sensor networks. The principal fields are related to temperature and humidity monitoring, surveillance, rescue operations and home automation. Most of the applications that require large-scale networks, such as the detection of forest fires, use high range transmission standards like IEEE 802.11b. Other applications, such as home automation that require less transmission range, use other standards, such as IEEE 802.15.4 related to ZigBee specifications. This standard is normally used for home automation and industrial monitoring applications. In fact, many works have demonstrated that conventional wireless standards such as Bluetooth or \"WLAN\" [2, 3] are not suitable to be used in this type of network. It has also been shown that the best standard taking into consideration the constraints of indoor networks is IEEE 802.15.4 [4]. Furthermore, the ZigBee network is has the least, compared with other wireless networks, SNR [5; 6], which makes it the best standard for indoor applications, where noise has a strong presence, especially in industrial manufacturing.  
It is also important to note that several works have been conducted to improve the energy efficiency of sensor networks by enhancing routing protocols, topology control and data aggregation, and the results are confirmed using simulation tools such as Ns-2, Omnet, MATLAB, etc. [7; 8]. However, building energy-efficient hardware has not yet gained much interest from the research community. Consequently, most of the commercialized sensor nodes have a high consumption level, energy still being an unresolved problem. In addition, the commercialized nodes do not give any possibility to improve the performances related to the physical and MAC layers, namely the registers of transmission and reception, the size of packets, and others.  
Thus, the first challenge that we tackle in this paper is to design a prototype of the sensor node that reduces the energy consumption while maintaining a high level of performance. As a matter of fact, the idea was to use a combination of a ZigBee radio transceiver provided by Microchip [9] and an \"Arduino\" microcontroller [10]. Our designed node showed satisfying results in terms of energy saving and the reliability of data processing. Secondly, we focus on topology construction to enhance the performances of the sensor network. We developed an improved cluster-tree topology based on the minimum spanning tree (MST) that we called minimum spanning cluster-tree (MST).  
The remainder of the paper is organized as follows; Section 2 presents some concepts related to our contribution, namely ZigBee specifications and graph theory concepts. Section 3 describes our hardware architecture based on the ZigBee transceiver and Arduino microcontroller, as well as an overview of our system. In Section 4, we treat our developed topology based on minimum spanning trees. Section 5 evaluates the performances of the system by presenting our experimental scenario and results. Finally, Section 6 concludes the paper.