Precision agriculture monitoring system using wireless sensor network and Raspberry Pi local server

Flores, Kristoffer; Butaslac, Isidro M.; Gonzales, Jon Enric M.; Dumlao, Samuel Matthew G.; Reyes, Rosula

doi:10.1109/tencon.2016.7848600

Cited by 50 publications

(26 citation statements)

References 3 publications

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“…In general, most of the sensor nodes used to monitor soil data (such as temperature, humidity, and matric potential) and weather data (such as temperature and relative humidity) are operated using open, low-cost hardware platforms such as the Arduino [10][11][12][13][14] or Raspberry Pi [15][16][17]. Zigbee [11,[17][18][19], LoRa [16], Wifi [20], Bluetooth [14], GSM [12], and GPRS [21] are the predominant wireless technologies used.…”

Section: Data Gatheringmentioning

confidence: 99%

Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Campos

Rocha²,

Gondim

et al. 2019

Sensors

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Irrigation is one of the most water-intensive agricultural activities in the world, which has been increasing over time. Choosing an optimal irrigation management plan depends on having available data in the monitoring field. A smart agriculture system gathers data from several sources; however, the data are not guaranteed to be free of discrepant values (i.e., outliers), which can damage the precision of irrigation management. Furthermore, data from different sources must fit into the same temporal window required for irrigation management and the data preprocessing must be dynamic and automatic to benefit users of the irrigation management plan. In this paper, we propose the Smart&Green framework to offer services for smart irrigation, such as data monitoring, preprocessing, fusion, synchronization, storage, and irrigation management enriched by the prediction of soil moisture. Outlier removal techniques allow for more precise irrigation management. For fields without soil moisture sensors, the prediction model estimates the matric potential using weather, crop, and irrigation information. We apply the predicted matric potential approach to the Van Genutchen model to determine the moisture used in an irrigation management scheme. We can save, on average, between 56.4% and 90% of the irrigation water needed by applying the Zscore, MZscore and Chauvenet outlier removal techniques to the predicted data.

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Section: Data Gatheringmentioning

confidence: 99%

Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Campos

Rocha²,

Gondim

et al. 2019

Sensors

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“…Agricultura [16], [17], [11], [18], [19], [20], [21], [22], [10], [14], [23], [24], [25], [15], [26], [27], [6], [28], [29], [30], [2], [4], [31].…”

Section: Documentos Encontradosunclassified

“…TIC [16], [11], [18], [32], [33], [21], [45], [7], [35], [36], [43], [15], [26], [5], [44], [38], [3], [46], [29], [39], [30], [41], [47], [48].…”

Section: Documentos Encontradosmentioning

confidence: 99%

Internet de las cosas aplicado a la agricultura: estado actual

et al. 2019

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Este artículo presenta una revisión actualizada de las diferentes aplicaciones de tecnologías enmarcadas en el internet de las cosas (IoT) en agricultura, mediante la recopilación de diversos documentos en las áreas de interés, y por medio de criterios de selección puntualizados, respondiendo preguntas específicas de investigación. La información recolectada se dividió en dos factores relevantes: en primer lugar, se identificaron las tecnologías de IoT aplicadas en agricultura divididas en capa de percepción y capa de red; por otra parte, se hizo énfasis en la búsqueda de desarrollos aplicados en América Latina, con especial cuidado en Colombia, para establecer la influencia de este tipo de tecnologías en la región. Finalmente, este trabajo pretende dar un panorama para futuras investigaciones, estableciendo los dispositivos y las tecnologías de IoT más recurrentes aplicadas en agricultura.

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“…In addition, the sensor nodes also sense environmental conditions for weather forecast and natural disaster happening probability. In these networks, the sensor nodes are categorized into coordinator and normal nodes to collect the data from the agricultural field [6]. The sensor nodes sense the required parameters and analyze the distance threshold (d Th ) and then forward the sensed data to the sink node by single-hop or multihop communication.…”

Section: Introductionmentioning

confidence: 99%

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

et al. 2020

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Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid-(GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.

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Precision agriculture monitoring system using wireless sensor network and Raspberry Pi local server

Cited by 50 publications

References 3 publications

Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Internet de las cosas aplicado a la agricultura: estado actual

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

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