A4NH / Animal Breeding / Animal Health / Computing / ILRI / Kenya / LiveGene / LIVESTOCK-FISH / Research

Introduction to ngombe-watch cow monitoring system

In the research of animal health and productivity, there is need to monitor the movement, temperature and restlessness of animals. We do believe that the well being of an animal can be inferred from its movement and restlessness. While it is hard to know the well being of an animal without collecting samples conducting biological tests, it is very possible to track and record the movement of animals and its restlessness and infer its well being.

With the advancement of technology and emergence of embedded systems, it has become feasible to record the restlessness of an animal.

These advancements led to  ngombe-watch – a cow monitoring system using waspmotes from libelium. Waspmotes are small embedded systems which can be hanged on animals necks and collect different sets of data and from analysis of this data deduce its state and movement. These waspmotes collects the following information from the cow on which they are hanged.

  • Accelerometer data
  • Temperature (outside)
  • GPS

The information is automatic sent to a server where processing is done and the data saved into an online database. Charts are then automatically generated to present the  received data from which the interested stakeholders can extract the information they are interested in. This information is useful because it can be used to tell the status of the cow regarding such aspects as:

  • Health
  • Productivity
  • Security – In terms of location

Cow profiles can also be built so as to come up with useful trends and relationships about the cow.

This blog is part of a series of blogs that will discuss and disseminate the progress we have made so far in developing a cow monitoring system.

Some information about the components of the system

Waspmote

The waspmote is a wireless sensor device that can be used to collect information from sensors and later transmit that information to a server for further processing. The same information can be used to make decisions within the waspmote.

The sensors that can work with the waspmote are among others:

Agriculture related sensors Air Temperature / Humidity,Soil Temperature / Moisture,Leaf Wetness,Atmospheric Pressure,Solar Radiation,Ultraviolet Radiation,Trunk Diameter,Stem Diameter,Fruit Diameter,Anemometer,Wind Vane,Pluviometer,Luminosity

Gases related sensors Carbon Monoxide,Carbon Dioxide,Oxygen,Methane,Hydrogen,Ammonia,Isobutane,Ethanol,Toluene, Hydrogen Sulfide,Nitrogen Dioxide,Ozone,Hydrocarbons,Temperature,Humidity,Atmospheric pressure,

Smart Metering sensors Current,Water flow,Liquid level,Load cell,Ultrasound,Distance Foil,Temperature,Humidity,Luminosity

Events sensors Pressure/Weight,Bend,Vibration,Impact,Hall Effect,Tilt,Temperature (+/-),Liquid Presence,Liquid Level,Luminosity,Presence (PIR),Stretch

Application examples:

  • In Agriculture

The waspmote can be used to monitor several aspects of the environment that affect plants.For plants growing in a green house the temperature, humidity are of utmost importance. The waspmote can be used to regulate the levels of humidity and temperature automatically e.g using a sensor when the temperature/humidity rises/lowers below a threshold. An already made project is the Agricultural Management Expert System. here’s the link. http://www.siegasystem.com/en/index.html

  • Gases

The waspmotes have been used to detect Forest fires through sensing of gases like carbon monoxide,carbon dioxide and also sensing the surrounding temperature and relative humidity. Here’s a link http://www.libelium.com/wireless_sensor_networks_to_detec_forest_fires/

At Animal BioSciences, we are using the waspmote to monitor the state of the cows.

Functional design Structure (For the impatient geeks):

1. Waspmote collects the data – GPS, Accelerometer and temperature and saves it to an SD card.

2. Waspmote sends this data to a server online.

3. The server receives the data and saves to a MySQL database.

4. The data is then visualized on a web page using graphs and google maps.

About the Author Telewa Emmanuel is a Research Fellow at ILRI, Animal Biosciences and Student of University of Nairobi with keen interest in Hardware and Software automation. He was supervised by Absolomon Kihara

About Absolomon Kihara: Absolomon is the Biorepository manager at ILRI. He has a passion is designing and developing systems that easens the burden of data and sample collection and deployment of embedded systems in research in general.

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