Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics

Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products.Agro-scientific Researc

A Reliable and Efficient Wireless Sensor Network System for Water Quality Monitoring

Wireless sensor networks (WSNs) are strongly useful to monitor physical and environmental conditions to provide realtime information for improving environment quality. However, deploying a WSN in a physical environment faces several critical challenges such as high energy consumption, and data loss.In this work, we have proposed a reliable and efficient environmental monitoring system in ponds using wireless sensor network and cellular communication technologies. We have designed a hardware and software ecosystem that can limit the data loss yet save the energy consumption of nodes. A lightweight protocol acknowledges data transmission among the nodes. Data are transmitted to the cloud using a cellular protocol to reduce power consumption. Information in the cloud is mining so that realtime warning notifications can be sent to users. If the values are reaching the threshold, the server will send an alarm signal to the pond\u27s owner phone, enable him to take corrective actions in a timely manner. Besides, the client application system also provides the feature to help the user to manage the trend of a physical environment such as shrimp ponds by viewing charts of the collected data by hours, days, months. We have deployed our system using IEEE 802.15.4 Standard, ZigBEE, KIT CC2530 of Texas Instrument, and tested our system with temperature and pH level sensors. Our experimental results demonstrated that the proposed system have a low rate of data loss and long energy life with low cost while it can provide real-time data for water quality monitoring

Development and evaluation on a wireless multi-gas-sensors system for improving traceability and transparency of table grape cold chain

There is increasing requirement to improve traceability and transparency of table grapes cold chain. Key traceability indicators including temperature, humidity and gas microenvironments (e.g., CO2, O2, and SO2) based on table grape cold chain management need to be monitored and controlled. This paper presents a Wireless Multi-Gas-Sensors System (WGS2) as an effective real-time cold chain monitoring system, which consists of three units: (1) the WMN which applies the 433 MHz as the radio frequency to increase the transmission performance and forms a wireless sensor network; (2) the WAN which serves as the intermediary to connect the users and the sensor nodes to keep the sensor data without delay by the GPRS remote transmission module; (3) the signal processing unit which contains embedded software to drive the hardware to normal operation and shelf life prediction for table grapes. Then the study evaluates the WGS2 in a cold chain scenario and analyses the monitoring data. The results show that the WGS2 is effective in monitoring quality, and improving transparency and traceability of table grape cold chains. Its deploy ability and efficiency in implantation can enable the establishment of a more efficient, transparent and traceable table grape supply chain.N/

Efficient Design and Deployment of Aqua Monitoring Systems Using WSNs and Correlation Analysis

The roots of innovation are extending towards every field to provide ace solution. We cater an ace solution for aquaculture, where their yields (shrimp, fish, etc.) depends on the ponds water characteristics. The parameters depending on water must kept at certain optimal levels for better cultivation of Aqua. The parameters of water extremely project alterations during the day and also alter depending upon the environmental conditions i.e., it is necessary to monitor these parameters with high frequency. We adopt wireless sensor networks to monitor aqua forms. This system consists of two modules, they are transmitter and receiver station. We navigate data to database at receiver station through the GSM. The graphical user interface was designed in such a manner that the observations are forwarded to the farmer as message in their respective local languages to their mobile phones. That alerts them in unhygienic environmental conditions for adopting suitable measures

PVIDSS: Developing a WSN-based Irrigation Decision Support System (IDSS) for Viticulture in Protected Area, Northern China

Abstract: The vineyard management is evolving from manual mode to automatic information management, especially in protected area culture mode. The conventional irrigation technology is a kind of the inefficient water usage technology. This paper developed PVIDSS: an irrigation system based on Wireless Sensor Network (WSN) to provide an effective way to improve the irrigation efficiency. Firstly, the interview, survey and document review were carried out to identify the main factors affecting the vine's growth and exact the system requirement, irrigation rules. Then, the architecture of PVIDSS was design based on the function requirement. Integrating the WSN based on ZigBee, the system monitors the key parameters of vineyard accurately, such as temperature and soil moisture, and calculates a precision irrigation based on field data and the rule of vine's water requirement. The system test shows that the WSN-based decision support system is accurate in data processing and easy to install and configure, which supports the development of water-saving agriculture

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings