Survey of prototyping solutions utilizing Raspberry Pi

Saari, Mohd Yusof; Baharudin, Ahmad Muzaffar bin; Hyrynsalmi, Sami

doi:10.23919/mipro.2017.7973568

Cited by 30 publications

(14 citation statements)

References 16 publications

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“…Due to their high customization capabilities, a popular WSN configuration, uses Arduino sensors [56] to generate environmental measurements and utilizes the ZigBee module for communication purposes, as described by Satyanarayana and Mazaruddin [57] and Papamichail et al [58], whilst extensively documented by Kooijman [59]. However, with the coming of IoT, more microcontrollers have come to light in order to support or even remotely control the Arduino processes, such as Raspberry Pis [60,61], which can be setup to act as sensors [62], gateways [63], databases [64], servers [65] or fog devices [66].…”

Section: Wsns In the Agricultural Domainmentioning

confidence: 99%

Wireless Sensor Network Synchronization for Precision Agriculture Applications

et al. 2020

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The advent of Internet of Things has propelled the agricultural domain through the integration of sensory devices, capable of monitoring and wirelessly propagating information to producers; thus, they employ Wireless Sensor Networks (WSNs). These WSNs allow real time monitoring, enabling intelligent decision-making to maximize yields and minimize cost. Designing and deploying a WSN is a challenging and multivariate task, dependent on the considered environment. For example, a need for network synchronization arises in such networks to correlate acquired measurements. This work focuses on the design and installation of a WSN that is capable of facilitating the sensing aspects of smart and precision agriculture applications. A system is designed and implemented to address specific design requirements that are brought about by the considered environment. A simple synchronization scheme is described to provide time-correlated measurements using the sink node’s clock as reference. The proposed system was installed on an olive grove to assess its effectiveness in providing a low-cost system, capable of acquiring synchronized measurements. The obtained results indicate the system’s overall effectiveness, revealing a small but expected difference in the acquired measurements’ time correlation, caused mostly by serial transmission delays, while yielding a plethora of relevant environmental conditions.

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Section: Wsns In the Agricultural Domainmentioning

confidence: 99%

Wireless Sensor Network Synchronization for Precision Agriculture Applications

et al. 2020

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“…Taking it a step further, the work in [81] focused on the development of a WSN using a Raspberry Pi as a base station. According to [82], there exists a plethora of research works in the literature that explore the potentiality of these devices in innovation and prototyping. In the case of [81], the Raspberry Pi acted as a database and web server for collecting and managing agricultural data, whereas, for communication purposes, the ZigBee standard was adopted.…”

Section: Emerging Technologies For Smart Agriculturementioning

confidence: 99%

Latency-Adjustable Cloud/Fog Computing Architecture for Time-Sensitive Environmental Monitoring in Olive Groves

et al. 2020

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The emerging and vast adoption of the Internet of Things (IoT) has sprung a plethora of research works regarding the potential benefits in smart agriculture. A popular implementation involves the deployment of Wireless Sensor Networks (WSNs), which embed low energy consumption sensory nodes to capture the critical environmental parameters prevailing on the farms. However, to manage the ever-increasing volumes of raw data successfully, new approaches must be explored. Under this scope, current work reports on the design and development of an IoT system, having in mind the case of olive groves, which are considered the dominant sector for agricultural activity in the Mediterranean Basin. The system incorporates the cloud/fog computing paradigm to equip the olive growers with a low-cost solution for accurate, reliable, and almost real-time monitoring of their crops. Its core is based on a three-layered network architecture, capable of dynamically balancing the generated load, by pushing cloud-elastic resources to the underlying fog network. As such, the premise of the approach lies in the conforming character of the system that allows for targeted alterations to its operational functionality to meet stringent latency and traffic load environmental monitoring constraints. To evaluate the performance of the proposed architecture, a demo prototype is developed and deployed in the facilities of the Ionian University. Experimental results illustrate the efficiency, flexibility, and scalability of the approach in terms of latency, achieving response time reduction across all platforms, a subject of the utmost importance when it comes to precision agriculture of the future. Moreover, it is shown that the system is capable of dynamic functionality adaptation, to meet network traffic load constraints, achieving high throughput (on average 95%) and addressing potential environmental dangers to olive oil production.

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“…Di sisi lain, berbagai perangkat komputasi bergerak (seperti ponsel cerdas dan komputer tablet) telah menggunakan prosesor berdaya rendah, berharga terjangkau dan cukup bertenaga untuk menjalankan aplikasi multimedia. Berdasarkan alas an diatas maka perlu dikembangkan aplikasi-aplikasi berbasis raspberry pi, contohnya adalah mesin survey kepuasan pelanggan (Saptadi, 2014), Raspberry Pi, memiliki perangkat lunak siap pakai dengan Linux sebagai sistem operasi (Saari et al, 2017). Selain itu, ada banyak komunitas dan grup pengguna yang tersedia online dimana pengembang dapat meminta bantuan dan dukungan.…”

Section: Pengantarunclassified

Pengembangan aplikasi raspberry pi sebagai mesin survei kepuasan pelanggan

Karsid¹,

Aziz²,

Apriyanto³

2020

CDS

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This customer satisfaction survey machine was created to facilitate the survey process that will be used in the framework of the feedback process. This feedback is used as an evaluation material to continuously improve servants. This machine is made of Raspberry Pi as a mini personal computer (PC), which is equipped with a push button switch button as a survey input, as well as a 32 inch TV screen as a display. The programming language used is python, with Graphic User Interface (GUI) using Tkinter programming. From the survey engine, it can be seen a report on the number of respondents taking the survey. In addition, this tool can record survey data and present it in graphical form as a report.

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Survey of prototyping solutions utilizing Raspberry Pi

Cited by 30 publications

References 16 publications

Wireless Sensor Network Synchronization for Precision Agriculture Applications

Wireless Sensor Network Synchronization for Precision Agriculture Applications

Latency-Adjustable Cloud/Fog Computing Architecture for Time-Sensitive Environmental Monitoring in Olive Groves

Pengembangan aplikasi raspberry pi sebagai mesin survei kepuasan pelanggan

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