JOURNAL OF MARINE SCIENCES & ENVIRONMENTAL TECHNOLOGIES Vol. 1, Issue No. 2 (December-2015)

Cowpea, Vigna unguiculata (L.) Walp is the most popular legume cultivated in tropical and sub-tropical countries because of its high nutritional value. The physicochemical properties of four local varieties of cowpea seeds (Cream 7, Kaha 1, Dokki 331 and Kafr El-Sheikh 1) in Egypt were studied. Length, major and minor diameter of seeds were in the range of 6.70-12.90 mm, 3.33-5.58 mm, and 3.18-4.65 mm while the grain weight of the seeds varied between 8.40 to 34.90 g. The results showed that Cowpea seeds contain a high value of crude protein in the range of 25.79 to 29.25%. Moisture, dry matter, fat, ash and crude fiber values were in the range of 8.57 to 10.07%, 89.93 to 91.44%, 0.79 to 3.18%, 2.72 to 3.73% and 1.92 to 3.37% respectively. Carbohydrate content varied between 53.56 to 57.36%. When Callosobruchus maculatus, the most destructive pest of stored leguminous seeds, was provided with these varieties of cowpea, the percentage of adults emerging differed with variety.


Introduction
Water pollution is one of the major threats for the green globalization, to overcome the water pollution, first is to detect the pollutant either in river water or sea coast.The classic way to detect the water pollution is by using laboratory test, and by using this laboratory system (Karl and Willig, 2007).The samples should be given to testing equipment operator, then technical report are generated for that sample only and for that period of time of sample collection.
The new technique of testing, is to place probes and data acquisition channel in the river water or sea to detect pollution remotely by using different wireless sensors connected to server on site to monitor physical or environmental conditions, such as temperature, pH, conductivity, and heavy metals.This new technology system is an efficient as technical and practical point of view, since it works with alarm thresholds signal generation, it allows the early identification of critical water input data, and continuous automated water quality monitoring over twenty-four hours daily of ten minutes' idle time of sample collection and result generation

Materials and Methods
The designed system is a mix of different high technology equipment's; it works together as one unit or as standalone unit to monitor water activities either as drinkable water resources or sea water resource.The type of sensors of course different in both cases, and each type of sensor and attached station is dedicated to certain task or tasks of monitoring.The system is composed of sensors dedicated for water monitoring parameters such as pH, Oxygen level, temperature, Daphnia and Algae toximeter, data acquisition channel for data handling and process, computer system with specific technical specifications, wireless data network for connecting slave station to the host, and main file server which connects all remote stations by Local Area Network (LAN), or Wide Area Network (WAN).The complexity of the system is mainly dependent on number of parameters to be monitored during twenty-four hours daily, and number of stations used to monitor, for example a coast.The benefits of this system that no laboratory operator is required to collect a sample, then analyze it in special laboratory located a way from sample picking place.All the process done automatically by auto sampler, where analysis and result are generated on the site, then transmitted to the next server towards the main sever to give an alarm either by Mobile Text Short Message (SMS) to supervisor of the system, or technical report showing threshold values limits reached.

Materials
The materials used in the design of this system are a set of detectors (bio monitors), dedicated computer with touch screen, servers, data acquisition channels, local and wide area network either wire or wireless connection.
Various sensor combined in dense sensor network to monitor pH, Oxygen level, temperature, Daphnia and Algae toximeters, and fish toximeter.

Daphnia Toximeter
These daphnia or fish toximeters are sensitive to detect toxic substances in water via computer assisted digital image analysis.The system observes daphnia commonly known as

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ISSN: 2413-5267 "water fleas" in drinkable water, or fish in salty water (like sea water) under the influence of constantly running sample water, and to detect hazardous compounds in water from rivers (source-water protection) or sea (Martinez et al., 2004).Plants, distribution systems and production drains to preserve human health and to monitor water as shown in Figure (1).

Algae Toximeter
It is online Biomonitoring using Green Algae, it is fast and sensitive detection of toxic substances in water.The Algae Toximeter continuously monitors water for the presence of toxic substances.Standardized algae are mixed with the sample water and the instrument detects the photosynthetic activity of the algae (Martinez et al., 2004).Damage to the algae, caused e.g. by herbicides, causes a reduction in algae activity and activates an alarm above a pre-defined threshold, as shown in Figure (2).The measurement procedure requires the water samples be almost continually pumped into the Algae Toximeter, in which the concentration and the activity of the naturally occurring algae are determined.A precisely defined amount of algae from the fermenter is then added to the measuring chamber by way of a loop.The activity of the added algae remains constant as long as no toxic substances are present.If any toxic substance is present, its interaction with the photosynthesis center leads to an inhibition of algal activity.The dimensions of the inhibition can be estimated by comparing the algal activity with and without water sample (Mainwaring et al., 2002).

Servers and Local Computers
It consists of three major components: System site, System server, and System Client.The first one located at the site of measurement, while the second is to collect data in database

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ISSN: 2413-5267 from sensor resources, and the last is the way to view data and result of different locations in one monitor.All the hardware technical specifications of these system is showed in Table (1).

Local and Wide Network
The local network that connects system site to server in short distance by 100 Mbps speed of connection, and by using modem or wireless connection if the biosensor is a way from system site.The web based protocol is cloud that connects all the system, also the possibility to use Global System for Mobile (GSM) to connect remote stations to main server to send alarms or short status report.

Methods
The design of the system is divided to three main categories, the first one is system site which includes the Biosesnsors with data acquisition channel, and computer system which continuously collects data, status messages, and error reporter from the installed measuring systems in the measuring stations.The data records are buffered on the computers and are then transmitted via the Internet to system server as shown in Figure (3).The system server receives data and status messages from all measuring stations, then collected, and stored in an Oracle database.The system server automatically evaluates incoming data if the alarm index points to a suspicious water condition, then the responsible users are informed automatically by SMS and email.The system client displays transmitted data, evaluates and validate, then transmitted via the modem, and with little effort the client can be configured in such a that user can obtain the measured value of all measure and necessary for an assessment of water quality within shortest possible period of time, and generating graphical representation report as shown in Figure (4).

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ISSN: 2413-5267 Sample water (0.5 -2 l/h) continuously runs through the measuring chamber containing the daphnia or fish.The live images obtained using a CCD-camera are evaluated online with an integrated PC to analyze changes in the behavior of the daphnia/fish.If the change is statistically significant, an alarm is triggered.The method of image analysis enables a series of measurement methods and plausibility tests to assess the daphnia's/fish behavior using different criteria (Akyildiz et al., 2005).Toxicity index is major concept of evaluation of certain measures, such as speed or height, and changes in these measurements.Only when 2 or more of the measurements simultaneously show unusual results within a fixed period of time, Daphnia/fish Toxic data trigger an alarm.Toxicity detection due to video analysis of daphnia/fish behavior, and measurement is by using video image analysis, and sample volume of 200 l/hr, while the sensitivity to toxin is shown in Table (2), with regard to the following: average swim speed, speed distribution, swim height, average distance, fractal dimension of paths, curviness, turns, number of daphnia/fish, distribution in chamber, and size of daphnia/fish.

Flow of Work Processing
The flow of work processing of designed system is as follow: 1. Toxic substance is emitted into river or sea coast for example after disaster at tanker, chemical factory, or something else. 2. The system site reads the value and transmits them to system IT (Information Technology), then alarm index "warning" or "announcement stage" is created.3. Values and alarm index are transmitted via internet to system server.4. System server evaluates alarm index as significant.The administrator user is notified by SMS and email.Automatic sampling in the measuring station stores the suspected sample.5.The user analyses the values and alarm index via system client to ensure that with utmost probability a non-natural event has occurred (Ma et al., 2008).The user then obtains the samples from measuring station and initiates an analysis in the laboratory.6.The laboratory delivers an analysis of the samples.7. The user immediately informs the authority responsible for the warning and alarm plan.
The Laboratory Information Management System (LIMS) as shown in Figure ( 5) is the backbone of networking, data management and processing.It is a high-performance, immediately ready to operate laboratory information management system, and able to process the entire range of daily laboratory tasks efficiently and reliably from different resources and converting it to graphical presentation.

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ISSN: 2413-5267 The networking of system clients works on TCP/IP (Transmission Control Block-Internet Packet) protocol, and connected to system server with attached Oracle data base server, and the system protected by firewall for security reason towards system clients.The system site always located a way from the system server and it is connected over internet as data backbone, as shown in Figure ( 6).

Result
Actually this is study is a plane for a new monitoring method of pollution using smart sensors design and still not applied in Libyan environment, but as engineering point of view works perfectly.This system design is practical and novel, and could be applied also to monitor water resources for other interested parameters also, and this is the main advantages of using it: -Twenty-four hours' parameters monitoring.
-Multi-level of warning starting from administrator to user.
-No sample collecting and shipping to the laboratory.A technical comparison is done to compare the different smart sensor platform with respect of accuracy, measurement technique, orgasm used in measurement, and application as shown in Table (3).

Discussion and Conclusion
This system design is practical and novel, and could be applied also to monitor water resources for other interested parameters also the may affect the environment.
The conclusion is that this system is hybrid system because it is combination of different high technologies like Computer, data communication, Laboratory Information Management System (LMS), Biology, Digital image processing, security and alarming.The system is very effective and practical as long as there are good data communication backbone.The system could be upgraded to monitor air, and to monitor water if there are nuclear pollution, or any other interested parameter as shown in Figure ( 7).

Figure 1 .
Figure 1.Daphnia Toximeter station 24/24 Smart Stations for Pollution Monitoring Sea Coast or Artificial RiverFaculty of Marine Resources, Alasmarya Islamic University, Libya.

Figure 3 .
Figure 3. Overall system diagram of System site, Server site, and Client site with data flow direction

Figure 4 .
Figure 4. Sample of online graphical representation of Toxicity index value fluctuation 24/24 Smart Stations for Pollution Monitoring Sea Coast or Artificial RiverFaculty of Marine Resources, Alasmarya Islamic University, Libya.

Figure 5 .Figure 6 .
Figure 5. System connection structure using LIMS (Lab.Information Management System) 24/24 Smart Stations for Pollution Monitoring Sea Coast or Artificial RiverFaculty of Marine Resources, Alasmarya Islamic University, Libya.

Table 1 .
Recommended system Computer Hardware specifications Faculty of Marine Resources, Alasmarya Islamic University, Libya.

Table 2 .
Sensitivity to toxins in Daphnia & Fish toximeter station

Table 3 .
Toximeter Comparison of different Toxisensors used