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Smart Agriculture Project Ensures Crops Health and Reduces Losses

 Smart Agriculture Project Ensures Crops Health and Reduces Losses - IoT ONE Case Study
Technology Category
  • Functional Applications - Remote Monitoring & Control Systems
  • Networks & Connectivity - Gateways
  • Networks & Connectivity - WiFi
  • Sensors - Humidity Sensors
  • Sensors - Level Sensors
  • Sensors - Temperature Sensors
Applicable Industries
  • Agriculture
Applicable Functions
  • Business Operation
Use Cases
  • Remote Asset Management
The Challenge

Traditional agriculture companies have applied for ages the same tools and processes that have become antiquated these days. Most of the organizations that work on the farming sector have realized the great potential that cutting edge technologies have to ease their daily works, reduce losses or improve the yield quantity and also product quality. Wireless sensor networks have opened a wide range in terms of possibilities for farmers and agricultural management organizations. Getting real-time information from different water, soil or air parameters of any field allows taking smart and strategic decisions to save resources and optimize yields.

About The Customer
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The Solution

All sensor nodes connect through a meshed wifi network, using WPA2 authentication. Data is sent to the Cloud in intervals that vary from 5 to 15 minutes. The nodes use HTTP to communicate with an on-site gateway. The gateway in turn communicates securely, using TLS1.2, with Agnov8’s cloud based SaaS platform. Agnov8’s multi-tenant SaaS is hosted on AWS Cloud Platform. Through the platform any user can access to each sensor module to review sensor measurement data based on their locations.The raw data captured by the sensors can be downloaded for business intelligence or other research purposes. The platform is being upgraded with new features to notify events by email or SMS to alarm customers.

Data Collected
Accuracy, Crop Conditions, Precision, Soil Moisture Meters, Water Level
Operational Impact
  • [Efficiency Improvement - Labor]
    Reduced human error
  • [Efficiency Improvement - Production]
    Improving crop yields
  • [Data Management - Data Accuracy]
    Improved reliability of readings
Quantitative Benefit
  • Instead of once a week, readings are now taken every 15 minutes providing valuable insight into daily, weekly and monthly water quality trends.

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