Smart dog feeder design using wireless communication, MQTT and Android client

Vania,; Karyono, Karyono; Nugroho, Isadora

doi:10.1109/ic3ina.2016.7863048

Cited by 25 publications

(8 citation statements)

References 2 publications

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“…Respecto de las soluciones basadas en Raspberry Pi y Arduino, Vania, Karyono y Hargyo [5] diseñaron un dispensador de alimento con Arduino Uno basado en el protocolo MQTT, con identificación de mascotas empleando etiquetas RFID (radio-frequency identification) que permite autenticar al perro que tiene acceso al dispositivo. Permite programar las porciones a través de una aplicación Android y está compuesto de una celda de carga que permite medir las porciones que el usuario configura.…”

Section: Estado Del Arteunclassified

Monitoreo y control remoto de un dispensador de alimento para mascotas basado en IoT

Alvarez

Altamirano

Lascano

et al. 2021

RITI

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The search for alternatives that facilitate the care and feeding of a pet has created the need to apply current technological development in this type of application, since pet owners have restricted time to stay with them due to their daily duties, studies, work or carelessness. In the region, acquiring an automatic device that dispenses food and water in the same equipment and includes remote monitoring through an app on a smartphone is challenging and can be expensive. Therefore, this work presents the development of an automatic device based on MQTT (Message Queuing Telemetry Transport) to dispense food and water for pets, capable of being monitored and controlled through a mobile device. By integrating multiple technologies and tools such as: programming languages, sensor and actuator management, Raspberry Pi, Arduino, CAD (Computer-Aided Design) design and 3D printing, this IoT (Internet of Things) solution allows to implement an innovative prototype that contributes to improve this social problem not only in our country but throughout the region. The functionality tests validate that the developed device has a short response time and that it allows pet owners greater independence and peace of mind.

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Section: Estado Del Arteunclassified

Monitoreo y control remoto de un dispensador de alimento para mascotas basado en IoT

Alvarez

Altamirano

Lascano

et al. 2021

RITI

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show abstract

“…This yielded a reduced set of 18 articles. Finally, we also eliminated studies exploring the use of robots for feeding animals such as dogs [25] and fish [26]. Our final result set of studies on the use of robots in food delivery, consisted of 16 articles.…”

Section: Literature Reviewmentioning

confidence: 99%

Drive Through Robotics: Robotic Automation for Last Mile Distribution of Food and Essentials During Pandemics

Sharma

Zanotti²,

Musunur³

2020

IEEE Access

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The COVID-19 pandemic unraveled the weak points in the global supply chain for goods. Specifically, people all over the world, including those in the most advanced nations have had to go without medical supplies and personal protective equipment. Scarcity of essentials increases anxiety and uncertainty exacerbating unproductive behaviors like hoarding and price gouging. Left to market forces, such unfair practices are likely to aggravate hardships and increase the loss of lives. Thus, there is a critical need to ensure safe distribution of food and essential supplies to all citizens to sustain them through challenging times. To this end, we propose a simple, affordable and contact-less robotic system for preparing and dispensing food and survival-kits at community scale. The system has provisions to prevent hoarding and price gouging. Design, simulation, and, validation of the system has been completed to ensure readiness for real world implementation. This project is part of an open-source program and detailed designs are available upon request to entities interested in using it to serve their communities.

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“…Complete list of surveyed papers, with scenario code and application classification Paper Application Scenario Paper Application Scenario [18] Smart agriculture 0000000 [19] Smart home 1032102A [20] Smart home 0000103 [21] Smart home 1101133 [22] Smart home 0011010 [23] Smart home 1132020 [24] Smart building 0020000 [25] Smart building 1132110 [26] Smart agriculture 0020000A [27] Smart home 1232120 [28] Water management 0021000 [29] Disaster management 1301210 [30] Smart home 0021000A [31] Smart vehicle 1332300 [32] Energy monitoring 0030000 [33] Playful furniture 2012010 [34] Energy monitoring 0031000 [35] Smart agriculture 2023200 [36] Smart home 0101003 [37] Smart city 2030103 [38] Playful furniture 0101123 [39] Smart city 2032013 [40] Smart healthcare 0130030 [41] Smart healthcare 2033020 [42] Smart healthcare 0131113 [43] Robot movement 2130033 [44] Learning device 0230023 [45] Smart healthcare 2133030 [46] Smart healthcare 0231020 [47] Smart building 3001200 [48] Smart healthcare 0312020 [49] Smart home 3022103 [50] Smart healthcare 0321210 [51] Smart city 3032100 [52] Smart healthcare 0322310 [53] Robot movement 3032200 [54] Smart healthcare 0331020 [55] Smart security 3032203 [56] Smart home 1002013...…”

Section: Table 13mentioning

confidence: 99%

An IoT sensor and scenario survey for data researchers

2019

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This work surveys Internet of Things (IoT) experimental research published since 2015. We summarize the IoT state of the art during the last 2 years and extract important data that we apply to enhance the analysis of IoT solutions. The IoT scenario presents a promising universe to data analysis. This raises a number of questions: which are its most popular applications? What is the definition of scale in an IoT application? What sensors are more often used and for what IoT applications? How can a researcher compare IoT scenarios? To investigate these concerns, this survey analyzes 2 years' worth of contributions made in three main scientific publishers. We focus on IoT experiments that were actually implemented using real equipment within one or more scenarios. Our first contribution is the classification of those IoT scenarios into seven main aspects. Each analyzed research study presents a specific configuration of a scenario's variables and sensors. Our second main contribution takes place after the scenario mapping phase. We identify as many as 19 common categories of data types in use. The interrelation among the scenarios and the data types from sensors should assist data researchers in understanding current IoT dynamics.

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Smart dog feeder design using wireless communication, MQTT and Android client

Cited by 25 publications

References 2 publications

Monitoreo y control remoto de un dispensador de alimento para mascotas basado en IoT

Monitoreo y control remoto de un dispensador de alimento para mascotas basado en IoT

Drive Through Robotics: Robotic Automation for Last Mile Distribution of Food and Essentials During Pandemics

An IoT sensor and scenario survey for data researchers

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