Strategi Digital Shelf Management UMKM  dengan Algoritma Apriori

Shofa, Mohamad Jihan; Widyarto, Wahyu Oktri; Wiliyanto, Reza; Mahirah, Alifia; Firmansyah, Faisal Ibnu

doi:10.24014/jti.v8i2.19005

Cited by 1 publication

(1 citation statement)

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“…The constraint of utilizing APIs is the long response time, making it impossible to obtain data in real time [13,15]. Long response time will not be a problem in systems that do not need real time, such as IoT-based systems for monitoring livestock conditions [16][17][18] and locker accupation in smart laboratories [19]. But for early landslide detection systems [20], mitigation systems for fire emergency response [21], and detecting phase sequence detection in 3-phase electrical systems with a frequency of 50-60Hz which need to compare wave data from the power source side with the load side, requiring data in real time.…”

Section: Introductionmentioning

confidence: 99%

IoT APIs: Time Response Optimization in Edge Computing Data Communication for Power Phase Detection System

Nursuwars,

Shofa,

Andang

et al. 2024

E3S Web Conf.

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The IoT-based phase detection system is one of the important innovations in monitoring and managing modern electrical systems. However, challenges arise in presenting real-time data communication in the context of edge computing through the use of APIs. The problem that arises is the length of response time required in the data communication process, which can hamper the efficiency and accuracy of the system. The main objective of this research is to design and implement an effective strategy to reduce response time in API-based IoT data communication in phase detection systems. The method adopted includes a thorough analysis of existing communication processes and the development of optimized algorithms to speed up response times. This research approach involves measuring the response time before and after implementing an optimized algorithm on the client side, which in this case is represented by an Arduino device. Experiments were conducted using realistic data communication scenarios to validate the effectiveness of the proposed approach. The experimental results show that by optimizing the communication algorithm on the client side, the response time in IoT data communications can be significantly reduced. The response time which originally reached 4 seconds, was successfully reduced to only 0.8 seconds after the implementation of an optimized algorithm. This result has the potential to increase the operational efficiency of the system and expand the application of this technology in a variety of applications that require a fast response time.

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