Design of Automatic Feeder for Shrimp Farming Based on Internet of Things Technology

<p class="02abstracttext">In shrimp farming, feeding is an important activity to achieve good shrimp growth. Manual feeding manually using hand is less effective due to unequal food distribution. Thus, an automatic feeder is required to dispense feed at predetermined time. The advantages of automatic feeder are cost-effective, low labour requirement, and can be applicable for large volumes of feed. Design of automatic feeder machine can influence the capacity and time controlling of the feeder. In this research, the automatic feeder was designed using a controlling time system based on Internet of Things (IoT) technology. During plant trial, The automatic feeding was scheduled at 7 am, 11 am, 4 pm, and 8 pm. This machine could throw shrimp food homogeneously up to 10 m far for 2,500 m<sup>2</sup> pond area. In shrimp farming, distribution of shrimp food in predetermined time becomes an important rule to achieve good shrimp growth.</p>

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THE DESIGN OF AUTOFEEDER USING POLY VINIL CHLORIDE (PVC) THROWER FOR SHRIMP POND

Coastal and Ocean Journal (COJ) ◽

10.29244/coj.4.2.83-88 ◽

2020 ◽

Vol 4 (2) ◽

pp. 83-88

Author(s):

A Marsha Alansar ◽

Setyawan Dwi Nugroho ◽

Rizqi Ilmal Yaqin

Keyword(s):

Electric Motor ◽

Cost Effective ◽

Shrimp Farming ◽

Test Results ◽

Shrimp Pond ◽

Important Thing ◽

Automatic Feeder ◽

Pvc Pipe ◽

Labor Requirements ◽

Predetermined Time

n aquaculture, mainly for shrimp farming, feeding is an important thing. Feeding manually with the hand is less effective and ineffective. Thus, an automatic feeder is needed to dispense food at a predetermined time. The advantages of automatic feeders are cost-effective, reduce labor requirements, and allow large volumes of feed to feed efficiently. Autofeeder is a modern fish feeder that can be used in several ponds. Therefore, in this research, the Autofeeder has been made with PVC pipe for the feed thrower. The test results show that the speed of the electric motor after loading is 2782 rpm. Meanwhile, the thrower maximum distance is 10 m. Keywords Autofeeder, thrower, and PVC pipe

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Application of Internet of Things Technology in the Urban and Rural Transportation

2020 International Conference on Computer Network, Electronic and Automation (ICCNEA) ◽

10.1109/iccnea50255.2020.00061 ◽

2020 ◽

Author(s):

Haixiang Li ◽

Xiaonan Wang

Keyword(s):

Internet Of Things ◽

Internet Of Things Technology

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Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽

10.3390/s21124034 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4034

Author(s):

Arie Haenel ◽

Yoram Haddad ◽

Maryline Laurent ◽

Zonghua Zhang

Keyword(s):

Internet Of Things ◽

Radio Frequency ◽

Real Life ◽

Computation Time ◽

Cost Effective ◽

Battery Life ◽

Cross Layer ◽

Security Level ◽

Cost Of Energy ◽

Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

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