<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Wireless Sensor Network (WSN) is known for its autonomous sensors, where it has been found to be useful during the development of Internet of Things (IoT) devices. However, WSN is also known for its limited energy supply and memory space, as it carries small-sized batteries and memory space. Hence, a data compression approach has been introduced in this paper with the purpose of solving this particular issue. This paper focused on the performance of the Arithmetic Coding algorithm. Temperature (Temp), Sea-Level Pressure (Pressure), stride interval (Stride), and heart rate (BPM) were chosen as the dataset in this project. Based on the results, the compression ratio of Temp, Pressure, Stride, and BPM were 0.428, 0.255, 0.217, and 0.159 respectively. From this analysis, BPM produced the best compression ratio. Undeniably, the Arithmetic Coding algorithm is one of the best methods to compress real-world datasets. Hence, by using this approach, it can reduce the usage of energy and memory space.</span><table class="MsoTableGrid" style="width: 444.85pt; border-collapse: collapse; border: none; mso-border-alt: solid windowtext .5pt; mso-yfti-tbllook: 1184; mso-padding-alt: 0in 5.4pt 0in 5.4pt;" width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr style="mso-yfti-irow: 0; mso-yfti-firstrow: yes; mso-yfti-lastrow: yes; height: 63.4pt;"><td style="width: 290.6pt; border: none; border-top: solid windowtext 1.0pt; mso-border-top-alt: solid windowtext .5pt; padding: 0in 5.4pt 0in 5.4pt; height: 63.4pt;" valign="top" width="387"><p class="MsoNormal" style="margin-top: 6.0pt; text-align: justify;"><span style="font-size: 9.0pt; color: black; mso-bidi-font-style: italic;">Wireless Sensor Network (WSN) is known for its autonomous sensors, where it has been found to be useful during the development of Internet of Things (IoT) devices. However, WSN is also known for its limited energy supply and memory space, as it carries small-sized batteries and memory space. Hence, a data compression approach has been introduced in this paper with the purpose of solving this particular issue. This paper focused on the performance of the Arithmetic Coding algorithm. Temperature (Temp), Sea-Level Pressure (Pressure), stride interval (Stride), and heart rate (BPM) were chosen as the dataset in this project. Based on the results, the compression ratio of Temp, Pressure, Stride, and BPM were 0.428, 0.255, 0.217, and 0.159 respectively. From this analysis, BPM produced the best compression ratio. Undeniably, the Arithmetic Coding algorithm is one of the best methods to compress real-world datasets. Hence, by using this approach, it can reduce the usage of energy and memory space.</span></p></td></tr></tbody></table>

Abstract. An Internet of Things (IoT) device is usually powered by a small battery, which does not last long. As a result, saving energy in IoT devices has become an important issue when it comes to this subject. Since power consumption is the primary cause of radio communication, some researchers have proposed several compression algorithms with the purpose of overcoming this particular problem. Several data compression algorithms from previous reference papers are discussed in this paper. The description of the compression algorithm in the reference papers was collected and summarized in a table form. From the analysis, MAS compression algorithm was selected as a project prototype due to its high potential for meeting the project requirements. Besides that, it also produced better performance regarding energysaving, better memory usage, and data transmission efficiency. This method is also suitable to be implemented in WSN. MAS compression algorithm will be prototyped and applied in portable electronic devices for Internet of Things applications.