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![Figure 2. The farming system architecture, proposed by [13]](profile/Sami-Hajjaj/publication/320366473/figure/fig3/AS:631644096561205@1527607096843/The-farming-system-architecture-proposed-by-13_Q320.jpg)
![Figure 3. General hardware architecture for the RHEA project, [14]](profile/Sami-Hajjaj/publication/320366473/figure/fig1/AS:588810974941184@1517394884879/General-hardware-architecture-for-the-RHEA-project-14_Q320.jpg)
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... many organizations and conglomerates, this renders agriculture robots impractical and infeasible. A visual repre- sentation of this situation is shown in figure 4. As such, the key to implementing practical agriculture robots, is solving the technological challenges associated with establishing the support infrastructure needed by agriculture robots. ...
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... Due to food security issues, agricultural robots are popular. To be practical, farm robots need affordable and dependable assistance [9]. Theoretical advances and cutting-edge technology are accelerating agricultural robot development. ...
This document represents the design and development of a multifunctional agricultural mobile robot aimed at automating several farming tasks, including soil moisture measurement, precise irrigation, seed planting, and grass cutting. The robot uses an Arduino Nano as its central controller, with capabilities to measure soil humidity across a range of 0-100%, controlled by moisture sensors. The robot's speed of operation is 0.5 m/s, and it can cover an area of approximately 100 m² per cycle. The robot is equipped with servo motors for accurate seed planting and grass cutting, and a simple smartphone application enables real-time monitoring and control of robot functions. The moisture sensors trigger the watering mechanism, while the robot precisely plants seeds at predefined intervals and utilizes a rotating fan blade for grass cutting, improving efficiency and reducing manual labor. The robot's seeding mechanism can plant seeds at intervals of 5 cm, enhancing planting precision. A mobile application developed via MIT App Inventor facilitates user interaction, enabling the activation of various functions like watering, seeding, and mowing, while providing live sensor feedback. This research highlights the potential of such systems in addressing labor shortages, resource optimization, and enhancing food security through precision agriculture.
... The European Union (EU) has been at the forefront of developing agricultural robotics, initiating several key prototype projects aimed at enhancing farming efficiency and productivity (Izdepskyi, 2016). This development includes establishing robust infrastructure, such as reliable wireless connections, effective human-robot interaction frameworks, and software-sharing platforms that facilitate seamless integration of technology into agricultural practices (Hajjaj & Sahari, 2016). ...
The intensifying demand for food production, driven by population growth and climate pressures, has placed a strain on agricultural systems worldwide, particularly in Africa and the European Union (EU). This paper presents a comparative analysis of the adoption of robotics in agriculture across these regions, exploring the current practices, limitations, and advancements shaping the future of sustainable farming. In Africa, limited infrastructure, high costs, and technological barriers hinder the integration of robotics, challenging smallholder farmers and reducing productivity. Conversely, the EU demonstrates more advanced adoption, supported by robust policy frameworks and technology infrastructure, although it faces challenges including workforce aging and the need for ethical guidelines in AI applications. This study highlights significant case studies within the EU, such as those in the Netherlands and Germany, showcasing the economic and environmental impacts of robotics in diverse farming models. The analysis extends to the benefits of robotics in increasing productivity and resource efficiency while reducing labor dependency, contributing to precision farming practices and environmental sustainability. The findings underscore the critical role of robotics in future agricultural systems, suggesting that while Africa faces more immediate barriers to adoption, targeted investments and policy adaptations could bridge these gaps. The study concludes by advocating for tailored, region-specific strategies to achieve sustainable agriculture through robotics, underscoring the technology's potential to address global food security challenges in Africa and the EU.
... There is a prevailing belief that advancements in robotics science and engineering will significantly transform the landscape of agriculture. Notably, global investment and research in this field are undergoing nearly exponential growth [25]. Table 1 provides a summary of both commercial and research-based robots within the past eight years developed for weed control using a variety of end effectors. ...
Weed infestations pose significant challenges to global crop production, demanding effective and sustainable weed control methods. Traditional approaches, such as chemical herbicides, mechanical tillage, and plastic mulches, are not only associated with environmental concerns but also face challenges like herbicide resistance, soil health, erosion, moisture content, and organic matter depletion. Thermal methods like flaming, streaming, and hot foam distribution are emerging weed control technologies along with directed energy systems of electrical and laser weeding. This paper conducts a comprehensive review of laser weeding technology, comparing it with conventional methods and highlighting its potential environmental benefits. Laser weeding, known for its precision and targeted energy delivery, emerges as a promising alternative to conventional control methods. This review explores various laser weeding platforms, discussing their features, applications, and limitations, with a focus on critical areas for improvement, including dwell time reduction, automated navigation, energy efficiency, affordability, and safety standards. Comparative analyses underscore the advantages of laser weeding, such as reduced environmental impact, minimized soil disturbance, and the potential for sustainable agriculture. This paper concludes by outlining key areas for future research and development to enhance the effectiveness, accessibility, and affordability of laser weeding technology. In summary, laser weeding presents a transformative solution for weed control, aligning with the principles of sustainable and environmentally conscious agriculture, and addressing the limitations of traditional methods.
... The way robots communicate is influenced by various factors such as the robot, application, and environment which affect the establishment of a communication protocol and the overall performance of the robots. Wireless communication protocols like WiFi [35], ZigBee [36], and Bluetooth [37] are frequently used in digital agriculture. ZigBee is used in agricultural robots that are used in plant health assessment due to hardware availability, low power consumption, and flexible communications models that permit both IP-based and more simplified serial-like messaging. ...
The vulnerability of plants to various threats, such as insects, pathogens, and weeds, poses a significant risk to food security, particularly before harvest. Mobile robots are used in digital agriculture as a breakthrough approach to address challenges in crop production, such as plant health assessment and drought stress detection. This chapter aims to explore the application of agricultural mobile robots equipped with advanced sensing technologies and computer vision algorithms, along with their key features, to enhance crop management practices. An overview of some the platforms with different steering mechanisms, sensors, interfaces, communication, and machine learning has been provided along with case studies on the use of robots for collecting data on plant health indicators such as physiological parameters, leaf coloration, and soil moisture levels. Recent trends in this area show that by utilizing machine learning techniques such as convolutional neural networks (CNNs) and support vector machines (SVMs), the collected data are analyzed to identify symptoms of plant diseases, nutrient deficiencies, and drought stress, facilitating timely interventions to mitigate crop losses. The integration of Internet of robotic things into existing practices are also discussed with respect to cost-effectiveness, scalability, and user acceptance.
... Therefore, there are various types of robotic system applications in individual agricultural environments [17]. The characteristics of agricultural production require robots in agricultural areas to possess considerable intelligence and flexible production capabilities to adapt to complex non-structural environments [18], such as discrimination and obstacle avoidance. Confronted with these obstacles, experts have shifted their research focus from the mechanical part to machine vision and artificial intelligence, striving to solve the intelligent problem of agricultural robots. ...
Agriculture plays a crucial role in development, especially in low-income countries where the sector is large in terms of both aggregate income and total labor force [...]
... Monica Jhuria and colleagues have pioneered in disease identification using image processing, developing two databases: one for storing existing disease images and another for processing new queries. Their analysis considers three key aspects: color, texture, and shape [11,15,16]. ...
... The agricultural practices where robots can be used are crop condition identification, chemical application, mobile manipulation through collaborative arms, collection of field data, and selective application of pesticides. Hajjaj and Sahari (2016) found that while the adoption of robotics technology can be challenging for farmers in the initial stages, it does have the potential to perform a range of tasks efficiently and effectively, thereby reducing the cost of cultivation significantly. Further, they argued for institutional support and capacity building among young farmers for greater adoption of robotics in agriculture. ...
The Indian agricultural sector has long struggled with issues relating to input quality and supply, scientific management of farms, post-harvest storage, transport and processing, marketing, environmental degradation, and market and weather-related risks. Further, Climate Change affects the nature of farming operations and their overall outcome by decreasing water supply, degrading arable lands, increasing pest infestation and crop diseases, and diminishing yield quality and quantity. “Digital agriculture” is often seen as having the capacity to alleviate these prolonged issues faced by farmers. It enables the farmer to make better decisions and farmers can receive real-time feedback on the outcomes of their choices. Digital agriculture helps farmers to empower under four categories viz. Agronomical perspective, Technical perspective, Environmental perspective, and Economic perspective. Several technologies like IoT, Smart sensors, UAVs, Artificial Intelligence (AI), and Robotics provide highly relevant real-time data, data analytics can help farmers make sense of and make important predictions like harvest time, disease and infection risks, production volume, etc. The Ministry of Agriculture & Farmers Welfare has also announced the Digital Agriculture Mission 2021–2025 to forward digital agriculture. Several private partnership Agtech startups emerged with innovations that combat the issues of farmers and made an impact on the life of the farmers. Moreover, digital agriculture helps in advancing the United Nations Sustainable Development Goals (SDGs). But adoption of digital technology may not be a viable option for small farmers, due to higher investment and lack of operational skills. This calls for awareness and capacity-building programmes on digital agricultural practices to minimize the cost of operation and develop necessary skills among farmers. This study is an effort to define the role of digital agriculture and its significance in the empowerment of farmers.
... Agriculture is one of the areas where robots have started to show their potential in various field operations [1,2]. Laborintensive work profiles and challenging work conditions may be addressed through robotic devices, thereby allowing laborers to be reallocated to higher skilled work. ...
This paper proposes a rover prototype designed for our ongoing work in the area of field robotics. The rover consists of a drive-unit as a fundamental building block. Two or more drive-units can be linked mechanically to form a rover with a desired shape and form. Here, we present a kinematic model for the rover in a generalized form for a given shape and form of the rover. This model allows us to translate the high level rover motion (linear and/or angular) commands into motor-level motion commands. We present our approach to design the modular rover system using Robot Operating System as a control framework. Furthermore, we present a ‘follow-the-leader’ mode where the follower rover uses a vision system to track and follow the leader at a predefined offset. In the later section we discuss the viability of this research for future field work in the human technology frontier by leveraging the advancements in robotics.
... Many outdoor robotic automation applications, such as solar farm inspection and maintenance [8][9][10], disaster response [11][12][13], agriculture [14] and city re-planning [15,16] need to cover very large areas of 1-40 acres. Traversing such expansive environments with a single mobile robot is very time-consuming or even impractical. ...
Teams of mobile robots can be employed in many outdoor applications, such as precision agriculture, search and rescue, and industrial inspection, allowing an efficient and robust exploration of large areas and enhancing the operators’ situational awareness. In this context, this paper describes an active and decentralized framework for the collaborative 3D mapping of large outdoor areas using a team of mobile ground robots under limited communication range and bandwidth. A real-time method is proposed that allows the sharing and registration of individual local maps, obtained from 3D LiDAR measurements, to build a global representation of the environment. A conditional peer-to-peer communication strategy is used to share information over long-range and short-range distances while considering the bandwidth constraints. Results from both real-world and simulated experiments, executed in an actual solar power plant and in its digital twin representation, demonstrate the reliability and efficiency of the proposed decentralized framework for such large outdoor operations.
... the Internet of Things (IoT) (Stamatiadis et al., 2020) and (Boursianis et al., 2020), geo-positioning systems (Muangprathub et al., 2019) and (Flaco et al., 2019), big data (Kamilaris et al., 2017) and (Bronson et al., 2016) unmanned aerial vehicles (UAVs, drones) (Tsouros et al., 2019), automated systems, and robotics are only a few examples. Smart farming is based on a precise and resource-efficient technique that aims to boost agricultural commodities production efficiency while also improving quality on a long-term basis (Hajjaj et al., 2016) and (Marinoudi et al., 2019). Smart farming, on the other hand, should provide added value to farmers in the form of more timely and accurate decision-making processes and/or more efficient extortion operations and management. ...
The need for precise, effective, and reliable measurement and monitoring of environmental parameters in greenhouses is critical for crop quality and yield. In the past few years, advanced senor methods garnered considerable study in the agriculture field. Capable and efficient use of intelligent sensors in a variety of activities is optimizing resource use while minimizing human interposition. Therefore, this review article aimed to provide significant knowledge about the detection and diagnosis of environmental parameters in greenhouses and the present state of remote communication utilizing intelligent approaches, as well as providing a broad overview of the field. A wide range of sensors and actuators are used extensively in advanced agricultural facilities like plant factories and greenhouses to monitor and regulate their environmental conditions. Temperature and humidity are the most important variables that affect plant growth. The ideal temperature range for healthy plant development is between 4°C and 30°C. Temperature and humidity sensors are widely used in greenhouses. CO 2 concentration is critical for root growth and respiration. Photosynthesis and other physiological processes need an adequate amount of light and a photoperiod. CO 2 sensors and light sensors are often used to monitor smart facilities. When it comes to nutrition monitoring, electrical conductivity (EC) and pH concentration are crucial factors to measure. The most frequent method of monitoring water quality and nutrient content is using pH sensors. Wireless communication such as ZigBee, LoRa, Bluetooth, WiFi, Sigfox, and GPRS/3G/4G technology is widely used for remote monitoring of the ambient environmental condition. The fast expansion of communication networks and the availability of a broad variety of new distant, proximal, and contact sensors are creating new options for farmers. The advancement of technology creates new opportunities for smart farming, and this review article will assist in the implementation of improved monitoring technologies in smart farming.
