<p>The
production of row crops in the Midwestern
(Indiana) region of the US has been facing environmental and economic
sustainability issues. There has been an increase in trend for the application
of fertilizers (Nitrogen & Phosphorus), farm machinery fuel costs and
decrease in labor productivity leading to non-optimized usage of farm-inputs. A
structured literature review describes Lean and Green practices such as
profitability (return on investments), operational cost reduction, hazardous
waste reduction, delivery performance and overall productivity might be adopted
in the context of Precision Agriculture practices (variable rate irrigation, variable
rate fertilization, cloud-based analytics, and telematics for farm-machinery
navigation). </p>
<p>The literature review describes low
adoption of Internet of Things (IoT) based precision agriculture practices,
such as variable rate fertilizer (39 %), variable rate pesticide (8%), variable
rate irrigation (4 %), cloud-based data analytics (21 %) and telematics (10 %)
amongst Midwestern row crop producers. Barriers for the adoption of IoT based Precision
Agriculture practices include cost effectiveness, power requirements,
communication range, data latency, data scalability, data storage, data
processing and data interoperability. Focused group interviews (n=3) with Subject
Matter Expertise (SME’s) (N=18) in IoT based Precision Agriculture practices were
conducted to understand and define decision-making variables related to
barriers. The content analysis and subsequent ISM model informed an action
research approach in the deployment of an IoT wireless sensor nodes for
performance improvement. The improvements resulted in variable cost reduction
by 94 %, power consumption cost reduction by 60 %, and improved data
interoperable and user-interactive IoT wireless sensor-based data pipeline for
improved adoption of Precision Agriculture practices. A relationship analysis
of performance data (n=2505) from the IoT sensor deployment empirically
validated the ISM model and explained the variation in power consumption for
mitigation of IoT adoption among producers. The scope of future research for
predicting IoT power consumption, based upon the growing season through
correlation was developed in this study.
</p>
<p>The implications of this research
inform adopters (row-crop producers), researchers and precision agriculture
practitioners that a Lean and Green framework is driven substantively by cost and power concerns in an IoT
sensors-based precision agriculture solution.
</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/17131526 |
| Date | 03 January 2022 |
| Creators | Gaganpreet Singh Hundal (11798345) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/EXPLORING_LEAN_GREEN_INTERNET_OF_THINGS_IOT_WIRELESS_SENSORS_FRAMEWORK_FOR_THE_ADOPTION_OF_PRECISION_AGRICULTURE_PRACTICES_AMONG_INDIANA_ROW-CROP_PRODUCERS/17131526 |
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