A New Solution to Perform Automatic Meter Reading Using ...

2014 IEEE 13th International Symposium on Network Computing and Applications

A new solution to perform Automatic Meter Reading using Unmanned Aerial Vehicle Jos´e Torres Neto

Daniel L. Guidoni

Leandro Villas

Institute of Computing University of Campinas S˜ao Paulo - Brazil Email: [email protected]

Computer Science Department Federal University of S˜ao Jo˜ao del-Rei Minas Gerais - Brazil Email: [email protected]

Institute of Computing University of Campinas S˜ao Paulo - Brazil Email: [email protected]

Abstract—Typically, electric power companies employs a group of employees known as meter readers to collect data of energy consumption of customers. To overcome the challenges and limitations of the literature approaches, we propose an automatic meter reading system based on Unmanned Aerial Vehicle and Wireless Sensors Networks. In our approach, each electric meter has one sensor node device with wireless communication capability and the Unmanned Aerial Vehicle flies the field in a predefined way to collect data from the wireless sensor nodes without having to visit each electrical meter. Simulation results show that our approach reduces the distance to perform the readings compared to literature solutions. We also present a use case analysis considering real parameters for meter readings.

I.

planning and deployment costs [8]. In this scenario, a wireless sensor network (WSN) can be used to create the AMR that can perform the readings and data routing [9], [10]. In this work we propose an automatic meter reading system based on Unmanned Aerial Vehicle (UAV) and Wireless Sensors Network (WSN). The AMR is created using bidirectional communication and a sensor device with wireless communication capability is embedded in each power meter to perform the automatic meter reading. The UAV flies over the target area broadcasting a request message. When a wireless sensor node receives the request message, it performs the power meter reading and creates a new message containing the costumer information as well as the power meter reading, and then, the wireless node sends the information to the UAV. When the UAV receives the costumer information, it can store the information of the power meter and power consumption or notify the base station using satellite communication or 3/4G from the cellular infrastructure.

Introduction

With the development of microelectronics technology and wireless embedded systems, new technological solutions are being developed to improve the people’s lifestyle. One of these solutions is the Automatic Meter Reading (AMR) System that aims to collect different types of data consumption from customers’ such as water, gas or energy consumption and the client bill is generated automatically [1], [2]. The AMR solution must have low power consumption, low cost and should be reliable and secure.

The remaining of this paper is structured as follows. In Section 2, we provide a general overview of the related work. Our proposal to perform automatic meter reading using UAV is described in Section 3. In Section 4, we present a performance evaluation and the simulation results. Finally, Section 5 concludes the paper with remarks and future work.

The technological advances in recent decades have significantly reduced the cost of the infrastructure needed for the installation of an AMR system, which has promoted companies to adopt this system. The fully functional AMR system correspond to the remote collection of customers’ information and transferring such information to a database for billing, analysis or troubleshooting [3]. As a result, the companies significantly reduces the cost of logistics and operation and the final price of the used service can be reduced [4].

II.

Several studies have been conducted in the context of Automatic Meter Reading (AMR) systems in order to propose methodologies for automatic data collection and also related to the communication of the devices [11], [12], [13], [7]. These studies are general and can be used for any kind of services, such as power, water or gas consumption since all the companies have the same problem.

The ultimate goal of a fully functional AMR system is to serve all types of meters and the system can be classified into three broad categories: [5], [6], [7]: (i) walk-by, in which the meter reader (an employee that caries a smartphone or a specific device containing the data collector) goes to each unit consumer; (ii) drive-by, where a vehicle equipped with an automatically remote data collector passes by each unit consumer; and (iii) fixed network, in which the energy meters are connected in a fixed network and the consumption data of each client are sent to the company that provides the service without the human intervention. The AMR systems that are constructed using a fixed network can use a wire or wireless technologies. The wireless technology is preferable due to the 978-1-4799-5393-6/14 $31.00 © 2014 IEEE DOI 10.1109/NCA.2014.33

Related Work

Peral et al. [12] proposes and evaluates a AMR system (powered by batteries) for water meters based on the IEEE 802.15.4. The data transmission and synchronization are based on a procedure defined in this standard. The network uses a tree topology with coordinators, routers and end-devices in different hierarchical levels. Each node (coordinator, router or end-device) has the same hardware for the communication among nodes. Moreover, the coordinator node has a IP connection with a fixed network (via cable or wireless) that is used to deliver the readings information to the water company. If the coordinator node loses its IP connection, all the collected 171

between UAV and embedded sensor nodes in power meters. The first phase is described in the left dotted rectangle (flight plan) and second phase (communication protocol) is described in the right dotted rectangle.

information can not be delivered, the authors did not present any solution considering this special case. Nhan et al. [11] proposed the deployment of low-cost wireless devices (communication range smaller than 40m) along the electricity meters. The set of these wireless devices create a Wireless Sensor Network (WSN) among the power meters. To perform the readings on the power meters, the authors suggest the use of wireless nodes embedded on public transport vehicles, reducing the reading cost. The motivation to use this strategy is based on the displacement of the public transport vehicles, that transverse a certain route. In this way, it is not necessary to employ any exclusive vehicle to perform the power meter readings. Besides these vehicles, the authors suggest the use of motorcycles (with an embedded wireless node) to perform the meter reading where we do not have public transportation. However, in some real scenarios, the authors pointed out that the wireless devices installed in the power meters, the network topology may be disconnected, since some power meters may be far from each other (greater than 40m). Based on these observations, we compare the solution proposed in this paper considering a vehicle that transverse all street in our scenario.

A flight plan is just a list of waypoints from the starting point to destination. In the proposed flight plan, the UAV flight starts at the point (0,0) and moves in a straight line to the right edge of the area (point (Xmax, 0)). Upon reaching the right end, the UAV moves in axis Y and the value of this displacement is limited by the transmission range of the UAV and sensors embedded in the power meters. After moving the Y axis, the UAV moves in a straight line to the left edge of the area (waypoint (0, Y current)). The UAV repeats these steps until it reach the end of the area (Xmax, Ymax). When this happens, the UAV returns to the origin point. The communication phase starts when a node receives a broadcast request from the UAV. In this case, it reads the current power consumption and replies the UAV’ request. When the UAV receives the response from power meter, it stores the information of the power meter and power consumption. Then, schedule the next broadcast request.

In this work we propose a new solution to perform automatic reading of electricity meters based on Unmanned Aerial Vehicles and Wireless Sensor Nodes to overcome the limitations of the current approaches. A more detailed description of the proposed solution is presented in the next Section.

IV.

Performance Analysis

A. Scenario configuration A simulation study was conduced to analyze the automatic meter reading system proposed in this work considering a target area. Our system was designed in order to collect the energy consumption of the customers. However, it can easily work considering other types of meters, such as water, gas etc. The simulations were performed using the Sinalgo Simulator [14]. The objective of our evaluation is to assess the performance of our approach, which combines the use of a Wireless Sensor Network and Unmanned Aerial Vehicle, the vehicle approach and the walk approach. In our approach, the UAV flies over the target area collecting the customers’ reading. In the vehicle approach (Car), we also consider a WSN, but a vehicle equipped with a wireless communication collects the customers’ reading. In the walk approach (Walk), a person carrying a smartphone or a palm walks by each street (considering the target area) to perform the custumers’ readings. The vehicle approach was based on the automatic meter reading proposed by [11].

III. Proposed Solution In our AMR system, each power meter is equipped with a sensor device with wireless communication capability. The UAV also has a wireless interface. As we can see in Figure 1, the UAV flies over the area of interest requesting the readings performed by each power meter, then the power meters equipped with wireless communication interface replies the UAV’s request. Our proposal is focused on automatic power meter reading. However, it can be applied to the supply of water and gas environments, which have the same problem.

This scenario was created considering a typical neighborhood in Brazil, where the width and depth of the lot is 15mx30m. To assess the results, we created scenarios with 1000, 2000, 4000 and 8000 power meter, where each sensor node represents a customer. The communication range of the sensor nodes is 50m. To have a fair comparison, the communication range of the UAV and the vehicle equipped with a wireless communication is also 50m. B. Simulation Results Fig. 1.

Table I shows the distance traveled by each approach (UAV, Car, Walk) considering different neighborhood sizes (number of customers). As our approach that combines the use of a wireless sensor network and unmanned aerial vehicle does not need to considers the streets to fly over the target area, its traveled distance is smaller compared to the other approaches.

Automatic Meter Reading Using Unmanned Aerial Vehicle.

The proposed solution is divided into two phases. The first refers to the UAVs flight plan to fly over the whole area of power meters. The second one is related to the communication

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For instance, when the network has 1000 nodes (customers), the traveled distance of the UAV is 1.53 and 4.29 times smaller compared to the Car and Walk approaches respectively. When the network has 8000 nodes, the traveled distance of the UAV is 1.71 and 5.41 times smaller compared to the Car and Walk respectively. This is due to the fact that for both Car and Walk approaches, their route is based on the city streets and this characteristic is not considered in the UAV flight plan, which only considers the customers’ meters. UAV CAR WALK

TABLE I.

1000 Nodes 5935 m 9262 m 25500 m

2000 Nodes 12169 m 20422 m 59700 m

4000 Nodes 20563 m 35902 m 108300 m

8000 Nodes 42076 m 73387 m 228000 m

TABLE II.

Travelled distance by UAV, Car and Walk approaches.

C. Use Case Analysis

Company information about readers and readings.

memory, wireless communication and battery), this model also has a GPS receiver, cameras, different types of sensors, LEDs etc. The GPS device is crucial for the flight plan, where the UAV must follow specific geographical points. Figure 3 shows the UAV accessories. It is also important to point out that the use of a WSN and UAV may be used to improve the quality of service provided by the electric supplier company. Since all meter has a sensor device, when the power system is stopped by a rain or thunder, the company can receive this information. In this case, the company can reduce the time to repair the problem and also to know where the service is not working. The UAV can also be used to record some problems or weather conditions.

In this section, we present a use case analysis of a real power supplier company. To carry out our analysis, we used real information of a power supplier company in the city of S˜ao Jo˜ao del-Rei, Minas Gerais state, Brazil. In this company, the reading are performed by set of company employee and this task is completely manual, i.e., the reader goes by walking to every house to verify the meter. In the end of the day, the reader update the company database with all collected information. After a few days, the customers receives the bill in their mail box by a special company to deliver letters. To reduce the cost of mailing the energy consumption bill, the company is equipping every reader with a portable print. In this case, after the reading, the customer bill is printed and delivered to the customer’s mail box. In this case, the cost to mail all bills is reduced, even with the additional cost to equip the reader with a portable print. However, because of the printing time, the number of readings performed by a reader in the latter case is increased. Table II shows the reader salary and the number of readings by a single reader considering the two cases described above (manual reading without a portable printer and manual reading with a portable printer). As we can see, when the bill is delivered after the reading, the number of readings performed by the reader is almost 50% smaller compared to when the bill is delivered after a few days, which will increase the number of company’s employees. It is important to point out that to perform 8000 readings, when the bill is printed after the reading, a single reader will take more than one month. As we showed in Section IV-B, our approach that combines a wireless sensor network and unmanned aerial vehicle takes less than 68 minutes.

Fig. 2.

Mikrokopter ARF Okto XL 6S12.

V.

However, to use our approach in real scenarios, we have to equip every meters with a wireless sensor device, which will increase the cost of our system. We also need a UAV (or a set of UAVs) to perform the readings. However, all these costs are introduced once and can be smoothed after a long-term. It is important to note that both sensor device and the UAV are off-the-shelf. In Brazil, the cost of a wireless sensor node based on the Arduino architecture is around US$ 60,00 and the cost of the UAV model Mikrokopter ARF Okto XL 6S12 is around US$ 8.000,00.

Conclusion

In this work, a new solution to perform automatic meter reading using Unmanned Aerial Vehicle and wireless sensors was presented. The UAV flies over the area of interest in a predefined way to collect data from electric meters (wireless sensor nodes) without having to visit each electric meter. Using our approach, the task of meter reading can be faster and with a low operational cost compared to literature solutions. It was also observed that our proposal solves the privacy problem, since the meter reader do not need to go into the house to perform the reading and also related problems such as limited access to the house. Based on simulation results, we

Figure 2 shows the described UAV model that could be used in real cases. Besides the basic components (processor,

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Fig. 3.

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Components of the mikrokopter ARF Okto XL 6S12

showed that out proposal has better results related to distance and time to perform all meter reading. The feasibility of our proposal was showed by a real use case analysis. We studied the manual meter readings used by Brazilian’s power supplier companies and showed that our system has great advantages even considering the initial cost to install each meter with a wireless sensor device as well as the UAV cost. It is also important to point out that the topic studied in this work has significant impact on real applications, such as wireless network design, low power consumption, low cost that can in fact improve nowadays remote meter reading solutions. As a future work, we are planning to evaluate our approach considering different scenarios with different density of meters, i.e., down town with buildings, rural areas. We are also planning to investigate different flight plans. VI.

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Acknowledgments

[14] Sinalgo, “Simulator for network algorithms,” 2014, distributed Computing Group ETH-Zurich.

We would like to thank CNPq, CAPES, FAPEMIG and FAPESP for the financial support.

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