Arsitektur Moisture Meter dengan Capacitive Sensing dan Serverless IoT Untuk Hidroponik Fertigasi

2021 ◽  
Vol 5 (2) ◽  
pp. 292-300
Author(s):  
I Wayan Aditya Suranata ◽  
I Gede Humaswara Prathama
Keyword(s):  
Sensor Technology ◽  
Data Logging ◽  
Chemical Fertilizers ◽  
Moisture Sensor ◽  
Technological Advances ◽  
Moisture Meter ◽  
Food Needs ◽  
Global Food ◽  
Great Danger ◽  
Drip Fertigation

The current agricultural systems generally uses chemical fertilizers as a growth booster in order to meet the global food needs of 7 billion people and all of their livestock. But unfortunately not all are aware of the great danger behind such an overuse, unmetered application of chemical fertilizers, freely in an open field for the survival of the planet and its population. Thanks to technological advances, especially in the field of instrumentation and communication technology, the problem of increasing efficiency and avoiding such overuse should be minimized properly. In this study, the researchers tried to apply capacitive moisture sensor technology and serverless Internet of Things to the moisture meter instrument in the hydroponic drip fertigation system with roasted husk planting media. Capactive sensor technology has the advantage of corrosion resistance when applied to planting media containing high humidity and low alkalinity. By using a serverless IoT architecture, it is possible to monitor from anywhere via the internet, without involving complicated and expensive infrastructure. Based on the results of the prototype testing, it is known that the instruments built can work properly. The results of monitoring system conditions such as temperature and free heap appear stable. The reading results of the two sensors also run steadily, without fluctuations and variations in the reading that exceed 5%. The process of remote monitoring and data logging to serverless IoT is monitored to be stable with a data recording success rate of 99.8%.

scholarly journals Can Organic Sources of Nutrients Increase Crop Yields to Meet Global Food Demand?

Agronomy ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 214 ◽  
Author(s):  
Jagadish Timsina
Keyword(s):  
Climate Change ◽  
Soil Fertility ◽  
Organic Farming ◽  
Crop Yields ◽  
Food Demand ◽  
Conventional Farming ◽  
Chemical Fertilizers ◽  
Organic Nutrients ◽  
On Farm ◽  
Global Food

Meeting global demand of safe and healthy food for the ever-increasing population now and into the future is currently a crucial challenge. Increasing crop production by preserving environment and mitigating climate change should thus be the main goal of today’s agriculture. Conventional farming is characterized by use of high-yielding varieties, irrigation water, chemical fertilizers and synthetic pesticides to increase yields. However, due to either over- or misuse of chemical fertilizers or pesticides in many agro-ecosystems, such farming is often blamed for land degradation and environmental pollution and for adversely affecting the health of humans, plants, animals and aquatic ecosystems. Of all inputs required for increased agricultural production, nutrients are considered to be the most important ones. Organic farming, with use of organic sources of nutrients, is proposed as a sustainable strategy for producing safe, healthy and cheaper food and for restoring soil fertility and mitigating climate change. However, there are several myths and controversies surrounding the use of organic versus inorganic sources of nutrients. The objectives of this paper are: (i) to clarify some of the myths or misconceptions about organic versus inorganic sources of nutrients and (ii) to propose alternative solutions to increase on-farm biomass production for use as organic inputs for improving soil fertility and increasing crop yields. Common myths identified by this review include that organic materials/fertilizers can: (i) supply all required macro- and micro-nutrients for plants; (ii) improve physical, chemical and microbiological properties of soils; (iii) be applied universally on all soils; (iv) always produce quality products; (v) be cheaper and affordable; and (vi) build-up of large amount of soil organic matter. Other related myths are: “legumes can use entire amount of N2 fixed from atmosphere” and “bio-fertilizers increase nutrient content of soil.” Common myths regarding chemical fertilizers are that they: (i) are not easily available and affordable, (ii) degrade land, (iii) pollute environment and (iv) adversely affect health of humans, animals and agro-ecosystems. The review reveals that, except in some cases where higher yields (and higher profits) can be found from organic farming, their yields are generally 20–50% lower than that from conventional farming. The paper demonstrates that considering the current organic sources of nutrients in the developing countries, organic nutrients alone are not enough to increase crop yields to meet global food demand and that nutrients from inorganic and organic sources should preferably be applied at 75:25 ratio. The review identifies a new and alternative concept of Evergreen Agriculture (an extension of Agroforestry System), which has potential to supply organic nutrients in much higher amounts, improve on-farm soil fertility and meet nutrient demand of high-yielding crops, sequester carbon and mitigate greenhouse gas emissions, provide fodder for livestock and fuelwood for farmers and has potential to meet global food demand. Evergreen Agriculture has been widely adapted by tens of millions of farmers in several African countries and the review proposes for evaluation and scaling-up of such technology in Asian and Latin American countries too.

scholarly journals A decade of detailed observations (2008–2018) in steep bedrock permafrost at Matterhorn Hörnligrat (Zermatt, CH)

2019 ◽  
Author(s):  
Samuel Weber ◽  
Jan Beutel ◽  
Reto Da Forno ◽  
Alain Geiger ◽  
Stephan Gruber ◽  
...  
Keyword(s):  
Past Research ◽  
Process Models ◽  
Sensor Technology ◽  
Future Research ◽  
Data Set ◽  
Technological Advances ◽  
Data Record ◽  
History Of ◽  
Diverse Data ◽  
And Control

Abstract. The PermaSense project is an ongoing interdisciplinary effort between geo-science and engineering disciplines started in 2006 with the goals to make observations possible that previously have not been possible. Specifically the aims are to obtain measurements data in unprecedented quantity and quality based on technological advances. This paper describes a unique ten+ year data record obtained from in-situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt Switzerland at 3500 m a.s.l. Through the utilization of state-of-the-art wireless sensor technology it was possible to obtain more data of higher quality, make this data available in near real-time and tightly monitor and control the running experiments. This data set (DOI: https://doi.org/10.1594/PANGAEA.897640, Weber et al., 2019a) constitutes the longest, densest and most diverse data record in the history of mountain permafrost research worldwide with 17 different sensor types used at 29 distinct sensor locations consisting of over 114.5 million data points captured over a period of ten+ years. By documenting and sharing this data in this form we contribute to making our past research reproducible and facilitate future research based on this data e.g. in the area of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models.

scholarly journals An IoT Based Smart Organic Drip Fertigation System for Eco-Friendly Agriculture using SVM Classifier and ThingSpeak

2020 ◽  
Vol 9 (4) ◽  
pp. 709-713
Keyword(s):  
Support Vector Machine ◽  
Soil Erosion ◽  
Support Vector ◽  
Svm Classifier ◽  
Chemical Fertilizers ◽  
Classification Result ◽  
Feature Vectors ◽  
Flow Feature ◽  
Classification Prediction ◽  
Drip Fertigation

a result, the proposed system helps in reducing soil erosion as only the required nutrients are injected via the drip system in order to reduce the usage of chemical fertilizers. In this paper, we use Support Vector Machine (SVM) to classify three (Temperature, Ph, Flow) feature vectors. The classification results will predict whether the obtained data is normal or abnormal and explore the accuracy of classification prediction by using SVM. Finally, the classification result obtained by applying SVM is uploaded to the ThingSpeak cloud.

scholarly journals Machine intelligence and the data-driven future of marine science

2019 ◽  
Vol 77 (4) ◽  
pp. 1274-1285 ◽  
Author(s):  
Ketil Malde ◽  
Nils Olav Handegard ◽  
Line Eikvil ◽  
Arnt-Børre Salberg
Keyword(s):  
Deep Learning ◽  
Data Analysis ◽  
Data Collection ◽  
Machine Intelligence ◽  
Information And Communications Technology ◽  
Sensor Technology ◽  
Marine Science ◽  
Technological Advances ◽  
Recent Developments ◽  
Earth’S Climate

Abstract Oceans constitute over 70% of the earth's surface, and the marine environment and ecosystems are central to many global challenges. Not only are the oceans an important source of food and other resources, but they also play a important roles in the earth's climate and provide crucial ecosystem services. To monitor the environment and ensure sustainable exploitation of marine resources, extensive data collection and analysis efforts form the backbone of management programmes on global, regional, or national levels. Technological advances in sensor technology, autonomous platforms, and information and communications technology now allow marine scientists to collect data in larger volumes than ever before. But our capacity for data analysis has not progressed comparably, and the growing discrepancy is becoming a major bottleneck for effective use of the available data, as well as an obstacle to scaling up data collection further. Recent years have seen rapid advances in the fields of artificial intelligence and machine learning, and in particular, so-called deep learning systems are now able to solve complex tasks that previously required human expertise. This technology is directly applicable to many important data analysis problems and it will provide tools that are needed to solve many complex challenges in marine science and resource management. Here we give a brief review of recent developments in deep learning, and highlight the many opportunities and challenges for effective adoption of this technology across the marine sciences.

scholarly journals Proximity data-loggers increase the quantity and quality of social network data

2012 ◽  
Vol 8 (6) ◽  
pp. 917-920 ◽  
Author(s):  
Thomas B. Ryder ◽  
Brent M. Horton ◽  
Mike van den Tillaart ◽  
Juan De Dios Morales ◽  
Ignacio T. Moore
Keyword(s):  
Social Network ◽  
Social Behaviour ◽  
Network Data ◽  
Data Logging ◽  
Breeding Bird ◽  
Proximity Data ◽  
Social Network Data ◽  
Technological Advances ◽  
Data Loggers ◽  
Pipra Filicauda

Social network analysis is an ideal quantitative tool for advancing our understanding of complex social behaviour. However, this approach is often limited by the challenges of accurately characterizing social structure and measuring network heterogeneity. Technological advances have facilitated the study of social networks, but to date, all such work has focused on large vertebrates. Here, we provide proof of concept for using proximity data-logging to quantify the frequency of social interactions, construct weighted networks and characterize variation in the social behaviour of a lek-breeding bird, the wire-tailed manakin, Pipra filicauda . Our results highlight how this approach can ameliorate the challenges of social network data collection and analysis by concurrently improving data quality and quantity.

scholarly journals Microbes as Biofertilizers, a Potential Approach for Sustainable Crop Production

2021 ◽  
Vol 13 (4) ◽  
pp. 1868
Author(s):  
Shaista Nosheen ◽  
Iqra Ajmal ◽  
Yuanda Song
Keyword(s):  
Crop Production ◽  
Cost Effective ◽  
Chemical Fertilizers ◽  
Promising Alternative ◽  
Sustainable Crop Production ◽  
Hazardous Chemical ◽  
Complex Forms ◽  
Global Food ◽  
Good Substitute

Continuous decline of earth’s natural resources and increased use of hazardous chemical fertilizers pose a great concern for the future of agriculture. Biofertilizers are a promising alternative to hazardous chemical fertilizers and are gaining importance for attaining sustainable agriculture. Biofertilizers play a key role in increasing crop yield and maintaining long-term soil fertility, which is essential for meeting global food demand. Microbes can interact with the crop plants and enhance their immunity, growth, and development. Nitrogen, phosphorous, potassium, zinc, and silica are the essential nutrients required for the proper growth of crops, but these nutrients are naturally present in insolubilized or complex forms. Certain microorganisms render them soluble and make them available to the plants. The potential microbes, their mode of action, along with their effect on crops, are discussed in this review. Biofertilizers, being cost effective, non-toxic, and eco-friendly, serve as a good substitute for expensive and harmful chemical fertilizers. The knowledge gained from this review can help us to understand the importance of microbes in agriculture and the ways to formulate these microbes as biofertilizers for sustainable crop production.

scholarly journals A decade of detailed observations (2008–2018) in steep bedrock permafrost at the Matterhorn Hörnligrat (Zermatt, CH)

2019 ◽  
Vol 11 (3) ◽  
pp. 1203-1237 ◽  
Author(s):  
Samuel Weber ◽  
Jan Beutel ◽  
Reto Da Forno ◽  
Alain Geiger ◽  
Stephan Gruber ◽  
...  
Keyword(s):  
Past Research ◽  
Process Models ◽  
Sensor Technology ◽  
Future Research ◽  
Data Types ◽  
Data Set ◽  
Technological Advances ◽  
Data Record ◽  
History Of ◽  
And Control

Abstract. The PermaSense project is an ongoing interdisciplinary effort between geo-science and engineering disciplines and started in 2006 with the goals of realizing observations that previously have not been possible. Specifically, the aims are to obtain measurements in unprecedented quantity and quality based on technological advances. This paper describes a unique >10-year data record obtained from in situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland, at 3500 ma.s.l. Through the utilization of state-of-the-art wireless sensor technology it was possible to obtain more data of higher quality, make these data available in near real time and tightly monitor and control the running experiments. This data set (https://doi.org/10.1594/PANGAEA.897640, Weber et al., 2019a) constitutes the longest, densest and most diverse data record in the history of mountain permafrost research worldwide with 17 different sensor types used at 29 distinct sensor locations consisting of over 114.5 million data points captured over a period of 10 or more years. By documenting and sharing these data in this form we contribute to making our past research reproducible and facilitate future research based on these data, e.g., in the areas of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models. Finally, the cross-validation of four different data types clearly indicates the dominance of thawing-related kinematics.

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