*Management Methods of Energy Consumption Parameters Using IoT and Big Data DOI: http://dx.doi.org/10.5772/intechopen.105522*

To evaluate the performance of the data transmission, the Wireshark program was used, which performs the analysis of protocols and data and allows visualizing the traffic that is happening on the network. The collection and sending of data from the IoT sensors, are scheduled every 5 seconds and are segmented into an average of 25 sections, as can be seen in **Table 13**, which shows the information obtained from the energetic measurements.

In addition, communication tests were carried out in sending and confirming packages for approximately 58.82 hours between the IoT sensors and the database server in a private network or VLAN, in order to verify the sending and receiving of data from where the results presented in **Tables 14** and **15** were obtained, which means that in the 58.82-hour interval of sending and receiving information, there was no loss or forwarding of packets, which provides good scalability and flexibility in the network.

The total information of the packet traffic in 1-second intervals during the measurement time had a duration of 58.82 hours; to visualize the information in a more detailed way, **Figure 12** shows the traffic analysis information in a window of duration of approximately 1.67 minutes; the time spaces between the peaks represent intervals when the IoT sensor is not communicating at all with the database server; for that reason, the packets delivered are 0. In addition, each signal peak refers to the number of packets that are sent and describes the number of sequences created during the transmission of information, that is, the number of measurements (280), (284) and (291) shown in **Table 13**, corresponds to eight of the thirty-one variables. In that case, the measurement the value two hundred and eighty (280), is the information


#### **Table 14.**

*Results of the data transmission performance of the meter block 6 third floor.*


#### **Table 15.**

*Performance results of meter block 6 basement data transmission.*

#### *Management Methods of Energy Consumption Parameters Using IoT and Big Data DOI: http://dx.doi.org/10.5772/intechopen.105522*

**Figure 12.**

*Traffic analysis graph of the measurement for 58.82 hours approximately in an interval of 1.67 minutes. Source: prepared by the authors.*

corresponding to the voltage in phase A that it was sent, this is the measurement corresponding to the first packet sent; in the measurement (284), it was sends the information contained from the voltage in phase B to the current in phase A; likewise, this is done with the measurement (291), this information is corresponding to the current in phase B is sent. It should be noted that the data frame is not it ends until the last measurement number packet (456) has been sent, which corresponds to the variable "angle\_fps". Finally, the duration time of each data frame corresponds to an average of 0.63 seconds and is composed of the time intervals when the sensor sends information and when the sensor does not share information with the database server.

This is the mature concept of a useful telemetry mechanism suitable for an interpreter who is familiar with electrical power consumption mechanisms to be able to perform, analyze, and interpret the information collected alluding to energy consumption. Therefore, those who are interested in this part know that it must be conditioned or improved and, in that case, must regulate the consumption generation processes; with this, a certifiable concept is allowed and is also supported by the green consumption standards of energy and by the ISO50001 standards that currently govern in Colombia.

There are currently different types of electrical network analyzers on the market, for which costs vary depending on customer needs. The designed modules prototypes, convert power transformers and the derived electrical distribution boards, into a class of smart object, and this allows to generate a network of sensors of low cost and with a reliable and safe data transmission method, in other words, when these components are in operation, there is not will be loss of information. Likewise, the customer can determine the measurement time required for acceptable results, and which electrical variables they want to acquire and know, furthermore, and if they want to use the transmission method remotely using the IEEE802.11 standard, or locally using the IEEE802.3 standard. In addition, the end customer can view the energy parameters through a graphical interface (dashboard) in a dynamic and interactive way.

The sensor network during the development of this work has a database server hosted on the university campus, which has a wide storage limit, for the integration of more sensors and the massive collection of more energy parameters having remote access.
