Precision Agriculture Monitoring System (PAMS)
The basic functionalities of a precision farming system should contain real-time
sensing of different crop production parameters likes crop, soil, or environment
parameters, etc.; positioning of sensing location and data accumulation; and
decision-making using the accumulated data. For precise monitoring of a farming
system, sensors are placed in the open crop field outside the control station and
positioned on static locations with unique sensor ID for network configuration and
deployment. PAMS allows continuous (24 Â 7 h) control of environmental data,
various thresholds, and health of network and alerts and produces different decisions from aggregated data. Thus, real-time monitoring is possible from anyplace
outside the field whenever it is required. Each sink node positioned in different
locations in the crop field is wirelessly linked to the central server. Each sink
gathers data from the field sensors and transmits a query request to the leader of the
cluster which forwards it to sink node in the similar way as event information is
forwarded. If it matches, it directs the event data back to the sink along the reverse
path (Rohith 2015).
There are some nanotechnology-based advanced concepts for precision farming.
Smart Dust Sensors
The development of autonomous wireless tiny sensors was started in 20 years back
by a robotics professor, Kris Pister, at University of California. These motes or
“smart dust” sensors utilize silicon etching technology for an onboard power supply,
computation abilities, detection, and then communication with other neighborhood
motes which make these motes efficient enough to transmit data wirelessly. Presently different companies (Crossbow Technologies with Millennial Net and Ember)
are manufacturing “smart dust” sensors, and Motorola, Intel, and Philips are also
planning to do so. Scientists are studying wireless sensor networks by installing
motes (approx. no. 120) for remote monitoring of microclimates around redwood
trees in Sonoma County, California (USA) (ETC report 2004).
Agrinfortronics
The effective blend of information and communication technology (ICT) and
mechatronics for agricultural applications is known as agrinfortronics (Opara
2002). It is presumed that the future of agriculture is highly dependent on the
knowledge economy which includes sensing, acquirement, analysis, storage, and
broadcast of precise and consistent data about the crop production environment
(Opara 2002). “Millipede,” a new concept of data storage (terrabit) based on
scanning probe, is reported by Vettiger et al. (2002) which provides ultrahigh density
with very small size and high data rate.
Ambient Intelligence
A very new discipline is emerging today, known as “ambient intelligence.” It is an
improved version of intelligence aimed at developing smart environments which
utilize artificial intelligence (AI) and sensors to foresee the individual needs and react
accordingly (Cook et al. 2009).
326
P. Pramanik et al.
The basic functionalities of a precision farming system should contain real-time
sensing of different crop production parameters likes crop, soil, or environment
parameters, etc.; positioning of sensing location and data accumulation; and
decision-making using the accumulated data. For precise monitoring of a farming
system, sensors are placed in the open crop field outside the control station and
positioned on static locations with unique sensor ID for network configuration and
deployment. PAMS allows continuous (24 Â 7 h) control of environmental data,
various thresholds, and health of network and alerts and produces different decisions from aggregated data. Thus, real-time monitoring is possible from anyplace
outside the field whenever it is required. Each sink node positioned in different
locations in the crop field is wirelessly linked to the central server. Each sink
gathers data from the field sensors and transmits a query request to the leader of the
cluster which forwards it to sink node in the similar way as event information is
forwarded. If it matches, it directs the event data back to the sink along the reverse
path (Rohith 2015).
There are some nanotechnology-based advanced concepts for precision farming.
Smart Dust Sensors
The development of autonomous wireless tiny sensors was started in 20 years back
by a robotics professor, Kris Pister, at University of California. These motes or
“smart dust” sensors utilize silicon etching technology for an onboard power supply,
computation abilities, detection, and then communication with other neighborhood
motes which make these motes efficient enough to transmit data wirelessly. Presently different companies (Crossbow Technologies with Millennial Net and Ember)
are manufacturing “smart dust” sensors, and Motorola, Intel, and Philips are also
planning to do so. Scientists are studying wireless sensor networks by installing
motes (approx. no. 120) for remote monitoring of microclimates around redwood
trees in Sonoma County, California (USA) (ETC report 2004).
Agrinfortronics
The effective blend of information and communication technology (ICT) and
mechatronics for agricultural applications is known as agrinfortronics (Opara
2002). It is presumed that the future of agriculture is highly dependent on the
knowledge economy which includes sensing, acquirement, analysis, storage, and
broadcast of precise and consistent data about the crop production environment
(Opara 2002). “Millipede,” a new concept of data storage (terrabit) based on
scanning probe, is reported by Vettiger et al. (2002) which provides ultrahigh density
with very small size and high data rate.
Ambient Intelligence
A very new discipline is emerging today, known as “ambient intelligence.” It is an
improved version of intelligence aimed at developing smart environments which
utilize artificial intelligence (AI) and sensors to foresee the individual needs and react
accordingly (Cook et al. 2009).
326
P. Pramanik et al.