Wireless sensor network (WSN) is one of the interesting issues in the information technology domain. It is used in various fields such as medicine, agriculture, meteorology, etc. that eases lots of difficult tasks to do but have some challenges too. Deployment is the greatest challenge in WSN that affects other features like coverage, connectivity, energy efficient and lifetime. Despite the importance of the deployment problem in WSN, to the best of our knowledge, there isn't any systematic literature review to give us systematical analyses the state-of-the mechanisms in this field. Therefore, this study reviewed the deployment mechanisms which have been used in WSN systematically. The deployment mechanisms can be classified into two main categories: deterministic and nondeterministic. Also, this study represents a comparison of the important techniques of the selected articles in each category to offer a guideline for further studies and new challenges. We also have noted some open issues for future research.

Deployment Strategies in the Wireless Sensor Networks: Systematic Literature Review, Classification, and Current Trends

Over the past few years, there has been significant interest in designing smart agricultural systems. The use of smart farming techniques can enhance the crop yield, while simultaneously generating more output from the same amount of input. But still, most of the farmers are unaware of the latest technologies and practices. In this paper a novel wireless mobile robot based on Internet of Things (IoT) is designed and implemented for performing various operations on the field. This proposed wireless robot is equipped with various sensors for measuring different environmental parameters. It also includes Raspberry Pi 2 model B hardware for executing the whole process. The main features of this novel intelligent wireless robot is that it can execute tasks such as moisture sensing, scaring birds and animals, spraying pesticides, moving forward or backward and switching ON/OFF electric motor. The robot is fitted with a wireless camera to monitor the activities in real time. The proposed wireless mobile robot has been tested in the fields, readings have been monitored and satisfactory results have been observed, which indicate that this system is very much useful for smart agricultural systems.

Internet of Things application for implementation of smart agriculture system

Robots have recently gained a great attention due to their potential to work in dynamic and complex environments with obstacles, which make searching for an optimum path on-the-fly an open challenge. To address this problem, this paper proposes a Genetic Algorithm (GA) based path planning method to work in a dynamic environment called GADPP. The proposed method uses Bezier Curve to refine the final path according to the control points identified by our GADPP. To update the path during its movement, the robot receives a signal from a Base Station (BS) based on the alerts that are periodically triggered by sensors. Compared to the state-of-the-art methods, GADPP improves the performance of robot based applications in terms of the path length, the smoothness of the path, and the required time to get the optimum path. The improvement ratio regarding the path length is between 6% and 48%. While the path smoothness is improved in the range of 8% and 52%. In addition, GADPP reduces the required time to get the optimum path by 6% up to 47%.

Optimizing robot path in dynamic environments using Genetic Algorithm and Bezier Curve

This article presents VineSens, a hardware and software platform for supporting the decision-making of the vine grower. VineSens is based on a wireless sensor network system composed by autonomous and self-powered nodes that are deployed throughout a vineyard. Such nodes include sensors that allow us to obtain detailed knowledge on different viticulture processes. Thanks to the use of epidemiological models, VineSens is able to propose a custom control plan to prevent diseases like one of the most feared by vine growers: downy mildew. VineSens generates alerts that warn farmers about the measures that have to be taken and stores the historical weather data collected from different spots of the vineyard. Such data can then be accessed through a user-friendly web-based interface that can be accessed through the Internet by using desktop or mobile devices. VineSens was deployed at the beginning in 2016 in a vineyard in the Ribeira Sacra area (Galicia, Spain) and, since then, its hardware and software have been tested to prevent the development of downy mildew, showing during its first season that the system can led to substantial savings, to decrease the amount of phytosanitary products applied, and, as a consequence, to obtain a more ecologically sustainable and healthy wine.

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VineSens: An Eco-Smart Decision-Support Viticulture System.

The technology development in wireless sensor network (WSN) offers a sustainable solution towards precision agriculture (PA) in greenhouses. It helps to effectively use the agricultural resources and management tools and monitors different parameters to attain better quality yield and production. WSN makes use of Low-Power Wide-Area Networks (LPWANs), a wireless technology to transmit data over long distances with minimal power consumption. LoRaWAN is one of the most successful LPWAN technologies despite its low data rate and because of its low deployment and management costs. Greenhouses are susceptible to different types of interference and diversification, demanding an improved WSN design scheme. In this paper, we contemplate the viable challenges for PA in greenhouses and propose the successive steps essential for effectual WSN deployment and facilitation. We performed a real-time, end-to-end deployment of a LoRaWAN-based sensor network in a greenhouse of the 'Proefcentrum Hoogstraten' research center in Belgium. We have designed a dashboard for better visualization and analysis of the data, analyzed the power consumption for the LoRaWAN communication, and tried three different enclosure types (commercial, simple box and airflow box, respectively). We validated the implications of real-word challenges on the end-to-end deployment and air circulation for the correct sensor readings. We found that temperature and humidity have a larger impact on the sensor readings inside the greenhouse than we initially thought, which we successfully solved through the airflow box design.

Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses.

Mobile robot navigation in smart environment has always been one of the most critical issues in robot research. Deployment of wireless sensor network (WSN) in new environment can provide the mobile robot with efficient aid of navigation and tracking. In this paper, we present a feasible scheme of WSN-aided mobile robot navigation which includes initial localization of mobile robot, orientation adjustment, network-layer path planning, motion tracking and correction based on RSSI in Grid-pattern WSN. Unlike other methods of robot navigation which might require a complex and intelligent robotic system for mapping and path planning, the aim of our method is to transfer complex environment detection and calculation from the robot to network and to decrease the reliance of intelligence on the robot itself. Experimental result shows that our proposed scheme is well-performed and can effectively navigate the robot equipped only with simply sensors for communication and obstacle avoidance.

RSSI-based mobile robot navigation in grid-pattern wireless sensor network

Recent developments in information technologies provide facility agriculture monitoring system a new perspective of networking and automation. This paper presents a new agriculture monitoring system based on WSNs (Wireless sensor networks) with IP cameras, which can be controlled remotely to have close vision of plants. WSNs can deploy freely, collect sensor data periodically to the control center, process and store historical data, which could facilitate clients and experts in agriculture to monitor the conditions in a large field. Traditional WSNs monitoring system only focused on environmental parameters, such as temperature and humility. We integrate video information and environmental data. Also the sleeping methods based on small-scale time synchronization and alarming mechanism of our system achieve better communication and less power consumption. Through experiments we validated the system in a greenhouse and outdoors fields in Hainan successfully.

A new agriculture monitoring system based on WSNs

This paper proposes a method of hierarchical WSN deployment and routing for fast localization Position-known anchor nodes form a static upper-layer network organization and several mobile nodes constitute the lower-layer network which need dynamic message exchange with the upper network In the upper static network, near-optimal routing table is allocated to each anchor node based on their known-position and the strength of signal for communication during network initialization Mobile nodes in the lower-layer can access to the upper network dynamically and at the same time report the RSSI value of nearby anchors to the control-center At the center, the computer will calculate the real-time location of the target based on the reported RSSI and node-IDs Algorithm presented in this paper is low cast, easy to implement and can be used for fast location estimation and motion tracking indoors and outdoors

Xiaoguang Zhao

Papers

RSSI-based mobile robot navigation in grid-pattern wireless sensor network

A new agriculture monitoring system based on WSNs

Deployment and Routing Method for Fast Localization Based on RSSI in Hierarchical Wireless Sensor Network