4.1 Recent Studies Done on Wireless Sensor Network
Now-a-days research is progressing on combining robotics and WSN for water
quality monitoring [67]. Ma et al. [68] provided a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with
mobile ultraviolet-visible spectrometer probes. Eichhorn et al. [69] and Vasilijević
et al. [70] designed an autonomous underwater vehicle (AUV) for analysis of water
quality parameters. Jadaliha and Choi [71] developed robotic sensors for monitoring temperature of swimming pool and gave a concept of Autonomous Surface
Vehicles (ASVs). Ferri et al. [72] also designed and developed ASV for monitoring
the coastal water quality. Liu et al. and Wu et al. [73, 74] designed a novel design
and multimodal locomotion control, prepared with many onboard sensors, which
permit it to be a self-propelled and self-contained system for a biomimetic robotic
dolphin capable of water quality monitoring. Robotic systems for water monitoring,
provide better spatial coverage for data collection using built-in GPS or sonar
positioning system as compared to fixed sensors. Ravalli et al. [75] studied a
bio-inspired artificial fish unit capable of changing its swimming patterns according
to the directives sent in form of chemical messengers from PANI-modified sensors.
The researchers [75] introduced the proof-of-concept for developing multi-sensors
fish robot as future core technology in aquaculture farm management. Zhang et al.
[76] proposed a novel scheme for autonomously sampling multiple water columns
using gliding robotic fish. The energy harvesting, wireless data transmission, harsh
aquatic environment is still a problem area when robots are to be deployed for
longer durations [77].
4.2 Smart Sensors
Smart sensors are intelligent devices which takes input from the environmental
factors and has built-in resources to detect and process the data. Smart sensors differ
from integrated sensors as they have built in programmable microprocessors.
Technically, a smart sensor has a sensing element, signal amplification and filtering
system in combination with a software for data processing and compensation [78].
Cloete et al. [10] reported an inexpensive, wireless, multi-sensor network for
measurement of physico-chemical water parameters with real-time monitoring.
Data from all the sensors is processed, analysed and then transmitted wirelessly to a
notification node which further informs the end user about the water quality. Yifan
and Peng [79] developed a wireless sensor network for water quality parameters
(temperature, turbidity, pH, dissolved oxygen and conductivity). Data is transferred
from monitoring nodes and data video base station to remote monitoring centre via
ZigBee and CDMA (code division multiple access) technology. Jiang et al. [80]
analysed water quality parameters (pH, conductivity, dissolved oxygen and temperature), an alarm was heard in the presence of a water contamination and data is
286
R. Soni et al.
Now-a-days research is progressing on combining robotics and WSN for water
quality monitoring [67]. Ma et al. [68] provided a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with
mobile ultraviolet-visible spectrometer probes. Eichhorn et al. [69] and Vasilijević
et al. [70] designed an autonomous underwater vehicle (AUV) for analysis of water
quality parameters. Jadaliha and Choi [71] developed robotic sensors for monitoring temperature of swimming pool and gave a concept of Autonomous Surface
Vehicles (ASVs). Ferri et al. [72] also designed and developed ASV for monitoring
the coastal water quality. Liu et al. and Wu et al. [73, 74] designed a novel design
and multimodal locomotion control, prepared with many onboard sensors, which
permit it to be a self-propelled and self-contained system for a biomimetic robotic
dolphin capable of water quality monitoring. Robotic systems for water monitoring,
provide better spatial coverage for data collection using built-in GPS or sonar
positioning system as compared to fixed sensors. Ravalli et al. [75] studied a
bio-inspired artificial fish unit capable of changing its swimming patterns according
to the directives sent in form of chemical messengers from PANI-modified sensors.
The researchers [75] introduced the proof-of-concept for developing multi-sensors
fish robot as future core technology in aquaculture farm management. Zhang et al.
[76] proposed a novel scheme for autonomously sampling multiple water columns
using gliding robotic fish. The energy harvesting, wireless data transmission, harsh
aquatic environment is still a problem area when robots are to be deployed for
longer durations [77].
4.2 Smart Sensors
Smart sensors are intelligent devices which takes input from the environmental
factors and has built-in resources to detect and process the data. Smart sensors differ
from integrated sensors as they have built in programmable microprocessors.
Technically, a smart sensor has a sensing element, signal amplification and filtering
system in combination with a software for data processing and compensation [78].
Cloete et al. [10] reported an inexpensive, wireless, multi-sensor network for
measurement of physico-chemical water parameters with real-time monitoring.
Data from all the sensors is processed, analysed and then transmitted wirelessly to a
notification node which further informs the end user about the water quality. Yifan
and Peng [79] developed a wireless sensor network for water quality parameters
(temperature, turbidity, pH, dissolved oxygen and conductivity). Data is transferred
from monitoring nodes and data video base station to remote monitoring centre via
ZigBee and CDMA (code division multiple access) technology. Jiang et al. [80]
analysed water quality parameters (pH, conductivity, dissolved oxygen and temperature), an alarm was heard in the presence of a water contamination and data is
286
R. Soni et al.