Design guidelines for ultra-low power gateways in environment monitoring wireless sensor networks

Byamukama, Maximus; Nannono, Janet Nakato; Ruhinda, Kabonire; Pehrson, Björn; Nsabagwa, Mary; Akol, Roselyn; Olsson, Robin; Bakkabulindi, Geoffrey; Kondela, Emmanuel

doi:10.1109/afrcon.2017.8095699

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…The motivation for this research comes from the preliminary observations of the battery SoC and voltage profiles of two WSN gateways. The first deployment was a low power WSN gateway, designed and implemented following the guidelines in [10]. The gateway uses the RS mote [11] as a sink node and the Electron 3G [12] as the uplink device.…”

Section: Methodsmentioning

confidence: 99%

New Techniques for Sizing Solar Photovoltaic Panels for Environment Monitoring Sensor Nodes

et al. 2019

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The development of perpetually powered sensor networks for environment monitoring to avoid periodic battery replacement and to ensure the network never goes offline due to power is one of the primary goals in sensor network design. In many environment-monitoring applications, the sensor network is internet-connected, making the energy budget high because data must be transmitted regularly to a server through an uplink device. Determining the optimal solar panel size that will deliver sufficient energy to the sensor network in a given period is therefore of primary importance. The traditional technique of sizing solar photovoltaic (PV) panels is based on balancing the solar panel power rating and expected hours of radiation in a given area with the load wattage and hours of use. However, factors like the azimuth and tilt angles of alignment, operating temperature, dust accumulation, intermittent sunshine and seasonal effects influencing the duration of maximum radiation in a day all reduce the expected power output and cause this technique to greatly underestimate the required solar panel size. The majority of these factors are outside the scope of human control and must be therefore be budgeted for using an error factor. Determining of the magnitude of the error factor to use is crucial to prevent not only undersizing the panel, but also to prevent oversizing which will increase the cost of operationalizing the sensor network. But modeling error factors when there are many parameters to consider is not trivial. Equally importantly, the concept of microclimate may cause any two nodes of similar specifications to have very different power performance when located in the same climatological zone. There is then a need to change the solar panel sizing philosophy for these systems. This paper proposed the use of actual observed solar radiation and battery state of charge data in a realistic WSN-based automatic weather station in an outdoor uncontrolled environment. We then develop two mathematical models that can be used to determine the required minimum solar PV wattage that will ensure that the battery stays above a given threshold given the weather patterns of the area. The predicted and observed battery state of charge values have correlations of 0.844 and 0.935 and exhibit Root Mean Square Errors of 9.2% and 1.7% for the discrete calculus model and the transfer function estimation (TFE) model respectively. The results show that the models perform very well in state of charge prediction and subsequent determination of ideal solar panel rating for sensor networks used in environment monitoring applications.

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Section: Methodsmentioning

confidence: 99%

New Techniques for Sizing Solar Photovoltaic Panels for Environment Monitoring Sensor Nodes

et al. 2019

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“…Other considerations like voltage and frequency of operation must be made. The full guidelines on low power design for environment monitoring WSNs have been published in [10]. We have been able to implement a reliable 55 mW system running sensor nodes based on the ATMEGA256RFR2 microcontroller from Radio Sensors AB [11] and the Electron 3G from Particle [12].…”

Section: Reducing Power Consumptionmentioning

confidence: 99%

“…The common AMS1117 buck regulator used to step-down to 3.3V in most embedded systems consumes 5mA under no load. In our implementation in [10], an active node consumes 12mA. Such an inefficient regulator would reduce battery life by 30 -40%.…”

Section: Quiescent Loadsmentioning

confidence: 99%

Powering environment monitoring Wireless Sensor Networks: A review of design and operational challenges in Eastern Africa

Byamukama

Bakkabulindi

Pehrson

et al. 2018

EAI Endorsed Trans IoT

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This paper discusses the various design and operational challenges that we have met in providing power to Wireless Sensor Networks (WSNs) deployed in environment monitoring in East Africa. While such deployments in African environments have a major advantage of abundant sunshine, both in intensity and duration, the same environments still present a number of unique challenges. With the various research initiatives in Africa being quite disjointed, a major problem is the lack of a unified knowledge base that communicates the current challenges and solutions in designing power systems for these WSNs. We implemented a WSN with several autonomous sensors and two types of gateways. We kept track of voltages, uptime and other diagnostic data. We combine our experiences from the study of these devices, and those of some others in the region and other developing countries and make recommendations where we have achieved good results and propose solutions where work is still in progress.

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The Energy Conservation and Consumption in Wireless Sensor Networks Based on Energy Efficiency Clustering Routing Protocol

Tesha

Amanul

2020

Advances in Intelligent Systems and Computing

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Design guidelines for ultra-low power gateways in environment monitoring wireless sensor networks

Cited by 4 publications

References 7 publications

New Techniques for Sizing Solar Photovoltaic Panels for Environment Monitoring Sensor Nodes

New Techniques for Sizing Solar Photovoltaic Panels for Environment Monitoring Sensor Nodes

Powering environment monitoring Wireless Sensor Networks: A review of design and operational challenges in Eastern Africa

The Energy Conservation and Consumption in Wireless Sensor Networks Based on Energy Efficiency Clustering Routing Protocol

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