Sustainable Agriculture with Self-Powered Wireless Sensing

Abstract

Agricultural sustainability is becoming more and more important for human health. Wireless sensing technology could provide smart monitoring in real time for different parameters in planting, breeding, and the food supply chain with advanced sensors such as flexible sensors; wireless communication networks such as third-, fourth-, or fifth-generation (3G, 4G, or 5G) mobile communication technology networks; and artificial intelligence (AI) models. Many sustainable, natural, renewable, and recycled facility energies such as light, wind, water, heat, acoustic, radio frequency (RF), and microbe energies that exist in actual agricultural systems could be harvested by advanced self-powered technologies and devices using solar cells, electromagnetic generators (EMGs), thermoelectric generators (TEGs), piezoelectric generators (PZGs), triboelectric nanogenerators (TENGs), or microbial full cells (MFCs). Sustainable energy harvesting to the maximum extent possible could lead to the creation of sustainable self-powered wireless sensing devices, reduce carbon emissions, and result in the implementation of precision smart monitoring, management, and decision making for agricultural production. Therefore, this article suggests that proposing and developing a self-powered wireless sensing system for sustainable agriculture (SAS) would be an effective way to improve smart agriculture production efficiency while achieving green and sustainable agriculture and, finally, ensuring food quality and safety and human health.

1. Introduction

Agricultural sustainability is becoming more and more important for human health. It emphasizes the protection of the ecological environment when conducting agricultural production. The harmonious coexistence between agriculture and the environment could be achieved by reducing the use of fertilizers and pesticides; protecting soil, water sources, and biodiversity; ensuring food quality and safety; and reducing the pollution and carbon emission of soil, water bodies, the atmosphere, breeding, and agricultural waste [1,2,3]. However, the agricultural system is complex, involving planting, breeding, and the food supply chain. Many factors such as environmental or biological parameters influence the production efficiency and sustainable development in actual agricultural systems [4,5,6]. It is necessary to monitor the agricultural parameters in real time to improve the production efficiency and sustainability in complex agricultural systems and finally ensure food quality and safety and human health.

Wireless sensing technology could provide smart monitoring in real time for different parameters in planting, breeding, and the food supply chain with advanced sensors such as flexible sensors; wireless communication networks such as third-, fourth-, or fifth-generation (3G, 4G, or 5G) mobile communication technology networks; and artificial intelligence (AI) models [7,8,9]. Precision monitoring can be implemented for actual agricultural environmental and biological parameters and provide accurate decision making for agricultural production management such as precision fertilizing and spraying pesticides in planting, precision feeding and disease prevention in breeding, and micro-environmental precision control and food preservation in the food supply chain. However, most conventional wireless sensing devices with different sensors deployed in the field of agricultural systems are not sustainable [10,11,12]. They need extra energy consumption from batteries and may need to be replaced manually at regular intervals and frequently when the batteries’ energy is exhausted. This power method would increase carbon emissions even more, even though it could improve precision and smart agricultural production efficiency. Therefore, it is necessary and important to reduce carbon emissions and further improve agricultural sustainability.

Sustainable energy harvesting-based self-powered wireless sensing could effectively provide a solution for sustainable agriculture smart monitoring. There are many kinds of sustainable, natural, renewable, and recycled facility energies such as light, wind, water, heat, acoustic, radio frequency (RF), and microbe energies that already exist in actual agricultural systems (as shown in Figure 1) [13,14,15,16,17,18]. They could be harvested by advanced self-powered technologies and devices with solar cells, electromagnetic generators (EMGs), thermoelectric generators (TEGs), piezoelectric generators (PZGs), triboelectric nanogenerators (TENGs), or microbial full cells (MFCs) [19,20,21,22,23,24]. These self-powered technologies could be applied for wireless sensing device power supply in complex agricultural systems of planting, breeding, and the food supply chain based on actual sustainable energy. Self-powered wireless sensing devices could form a wireless transmission network with a cloud center and users to implement smart agriculture monitoring and provide transparency, traceability, and safety assurance for farmers, enterprises, and consumers throughout the whole food supply chain.

Sustainable energy harvesting to the maximum extent possible could lead to the creation of sustainable self-powered wireless sensing devices, reduce carbon emissions, and result in the implementation of precision smart monitoring, management, and decision making for agricultural production. Self-powered wireless sensing would be an effective way to improve smart agriculture production efficiency while achieving green and sustainable agriculture. To better understand this method and provide a sustainable development reference in actual agricultural systems, the potential of self-powered wireless sensing systems for sustainable agriculture (SAS) and the challenges in its implementation route are discussed in this paper. The architecture for self-powered wireless sensing in sustainable agriculture is proposed in Figure 1. Sustainable energy from natural or artificial facility agriculture environments could be harvested as the self-powered supply for wireless sensing devices using different kinds of self-powered technology. Self-powered wireless sensing devices could be deployed in an actual planting, breeding, and food supply chain situation for monitoring sensor parameters and wirelessly transmitting them to the cloud center to achieve sustainable agriculture. All wireless sensing information could be made available for agricultural farmers, enterprises, and end consumers to improve production efficiency and quality in sustainable agriculture.

2. Wireless Sensing Parameters in Sustainable Agriculture

Wireless sensing has already played a crucial role in smart and sustainable agriculture. It could provide real-time and accurate data to assist agricultural farmers or enterprises in promoting sustainable agricultural development in precise management and decision making. Sustainable agriculture is a complex system that includes the planting, breeding, and food supply chain (as shown in Figure 1). There are many wireless sensing technologies, such as smart sensing, flexible sensing, the Internet of Things with wireless sensor networks, and so on, that could be applied to sustainable agriculture development [25,26,27]. The wireless sensing devices could be deployed in the actual situations of the planting, breeding, and the food supply chain for monitoring the sensor parameters, and wirelessly transmitted to the cloud center to achieve sustainable agriculture. All wireless sensing information could be available for agricultural farmers, enterprises, and end consumers to improve production efficiency and quality in sustainable agriculture. The wireless sensing parameters in sustainable agriculture are demonstrated in Figure 2.

2.1. Planting

Planting preparation, sowing and planting, field management, and harvesting are the main processes in agriculture planting. They are interrelated and jointly affect the growth, development, and yield of crops. The main parameters that need to be monitored during the planting process include soil parameters, meteorological parameters, crop growth parameters, and pest and disease parameters. Soil parameters include the soil nutrient status such as the total nitrogen (TN), the total phosphorus (TP), the total potassium (TK), the available nitrogen (AN), the available phosphorus (AP), and the available potassium (AK), the organic matter content, the pH, and the trace element content such as iron, zinc, manganese, copper, soil conductivity (EC), and moisture content [28,29,30].

Meteorological parameters include temperature, humidity, light intensity, and rainfall. A suitable temperature range could promote seed germination, plant growth, and fruit ripening. The humidity could affect plant growth. The high humidity may easily breed bacteria, and low humidity may lead to crop dehydration. Adequate light intensity is beneficial for photosynthesis, affecting crop growth and fruit sweetness. The rainfall monitoring could help prepare for flood or drought prevention in advance.

Crop growth parameters include the plant height, leaf area, stem thickness, and fruit growth status. These parameters directly reflect the growth status of crops and help detect growth abnormalities in a timely manner. The growth status of fruit could reflect the current nutrition status and make corresponding management measures in a timely manner. Disease and pest parameters include the types, quantities, and degrees of harm.

It is necessary and important to effectively improve the yield and quality of crops, and promote the modernization and sustainability of agriculture by monitoring these parameters and combining them with scientific planting management methods. Wireless sensing devices could integrate different kinds of planting sensors into the fields to acquire the soil parameters, meteorological parameters, crop growth parameters, and pest and disease parameters data, and send them to the cloud center for further process and decision making with smart models such as the AI. The smart decisions could be applied for the planting site further to guide the production. It could effectively reduce unreasonable behaviors such as excessive fertilization and pesticide application, improve the scientific efficiency of planting, reduce greenhouse emissions, and enhance agricultural sustainability in planting.

2.2. Breeding

Breeding includes various types of livestock breeding such as cattle, pigs, and sheep, poultry breeding such as chickens, ducks, and geese, aquacultures such as fish, shrimp, and shellfish, and some specialty breeding such as deer, minks, and otters. Breeding monitoring mainly includes the two aspects of environmental monitoring and animal growth physiology monitoring. ‌All these monitoring processes could be implemented by wireless sensing technology [31,32,33]. The breeding animals need a comfortable environment, as comfortable temperature, humidity, and air quality would influence their health growth. The precise monitoring of the breeding environment with wireless sensing could effectively improve the comfort environment control accuracy, reduce greenhouse gases and hazard gas emissions, and enhance environmental sustainability.

Another important monitoring process is the physiology and health of breeding animals such as the body temperature, heat rate, glucose, behavior, and so on. The animals’ health is very important to ensure their quality and improve their breeding efficiency. The physiology and health sensing data could be monitored in real time with wireless sensing in breeding. Breeding farmers or enterprises could master their physiology and health status so that they could carry out the scientific planning and decision making of daily management such as feeding, health prevention, disease diagnosis, and treatment. This monitoring process could not only make the breeding more precise but also reduce waste generation and carbon emissions. By implementing the breeding monitoring with wireless sensing, the breeding would not only be smarter, but also more sustainable.

2.3. Food Supply Chain

Agricultural production in the planting and breeding would be harvested for process, storage, transportation, and sale in the food supply chain. Consumers obtain the final fresh food from this complex food supply chain. The transparency and traceability of the food quality and safety in the supply chain are very important for enterprises and consumers. It could effectively reduce quality loss, food waste, and carbon emissions, and improve the sustainability of the food supply chain. Wireless sensing has provided a method to monitor the micro-environment fluctuation and quality variation in the supply chain, especially for the food cold chain [34,35,36]. Food cold chain keeps the fresh food processed, stored, transported, and sold at a low temperature all the time.

There are many micro-environmental parameters. They are the temperature, humidity, gas, and microbes. The micro-environmental parameters fluctuation would accelerate quality degradation. The food quality could be measured by the quality parameters of physical texture, chemical indicators such as the total volatile base nitrogen (TVBN), microbial indicators such as the total bacterial colony count (CFU), and sensory indicators such as the color and odor [37,38,39,40]. How to sense and monitor these micro-environmental parameters and build the correlation model between the micro-environmental parameters with food quality indicators in real time would be critical to improving the transparency, traceability, safety, and sustainability in the food supply chain. Wireless sensing could acquire the micro-environmental parameters sensing data by different sensors such as the physics, chemistry, and biology sensors, and wirelessly transmit them to the cloud center for further process and model building. Wireless sensing in the food supply chain could effectively promote the reduction of food loss and carbon emissions, and achieve green and sustainable development.

3. Self-Powered Technology in Sustainable Agriculture

3.1. Sustainable Energy

Sustainable energy is the key to realizing the self-powered supply for wireless sensing devices in sustainable agriculture. There are many sustainable energies that exist in actual sustainable agriculture systems. Sustainable energy mainly includes light, wind, water, heat, acoustic, RF, and microbe energies.

The light, wind, water, and heat energy could be from natural renewable energy and recycled energy in facility agriculture. The energy from the natural environment is clean and renewable energy, which is very important and necessary for sustainable agriculture production. The energy in facility agriculture such as the greenhouse, breeding, processing factory, and storage is another important energy to improve the agricultural efficiency all day. The energy in facility agriculture could not only provide crop growth, breeding, and facility environment control such as lighting, refrigeration, and heating, but it could also be recycled and harvested to further reduce carbon emissions and improve the sustainability of facility agriculture.

The acoustic, RF, and microbe energies exist in our daily surrounding environment all the time. Harvesting the surrounding acoustic energies such as noise, RF energy such as electromagnetic in wireless communication, and microbe energies such as environment or soil microbes could be another sustainable way to reduce the carbon emissions in actual agriculture systems, especially for the wireless sensing devices power supply in sustainable agriculture.

3.2. Self-Powered Technology

How to harvest sustainable energy in actual agriculture systems is another key to sustainable agriculture with self-powered wireless sensing. There are mainly six kinds of self-powered devices that could be used for sustainable energy harvesting. They are solar cells, EMGs, TEGs, PZGs, TENGs, and MFCs.

Solar cells are very useful for harvesting sustainable sunlight energy or artificial light energy in facility agriculture. There are many kinds of solar cells that are made of different materials such as mature and widely used silicon crystal materials, organic compound materials, and perovskite materials. The solar cells are usually made into an array structure to maximize the harvesting of light energy. However, conventional solar cells are mostly made with hard subtracts such as fluorine-doped tin oxide (FTO) and indium tin oxide (ITO), and they cannot be easily integrated into crops, animals, and foods for wireless sensing because of the agricultural biocompatibility. Therefore, the flexible and biocompatible solar cells developed and integrated would be a promising way for sustainable agriculture wireless sensing with the development of flexible electronic technology and biocompatible materials.

Sustainable energy such as wind, water, heat, and acoustic could work in the form of mechanical motion. They need to be harvested by converting mechanical energy into electrical energy. This convention could be implemented by EMGs, PZGs, and TENGs. EMGs are commonly and widely applied in our daily lives to generate electricity. The principle of EMGs is based on the phenomenon of electromagnetic induction. It could not only be used as large electric power for our daily life, but also be used as micro power supply for small electronic devices such as wireless sensing devices in sustainable agriculture. Sometimes the electromagnetic induction of EMGs could be also used for harvesting the RF energy with the electromagnetic variation in coils. The coils are the antenna. The antenna receives RF signals and converts them into electric energy for storage.

PZGs could convert mechanical energy into electrical energy using the piezoelectric effect. The piezoelectric effect refers to the polarization of certain materials when subjected to mechanical stress such as compression or tension, resulting in the generation of voltage. Due to the low voltage and short transmission distance, the output electrical energy of the PZGs is difficult to directly apply to some high-power devices. Their energy conversion efficiency is relatively low, and their applicable scenarios such as the mechanical vibration environment micro energy harvesting such as the acoustic, wind, and water in sustainable agriculture are also relatively narrow.

TENGs are the new generators recently based on the triboelectric and electrostatic induction effects. They consist of two materials with positive and negative electron binding abilities. Electrons will transfer from one material to another when they are in contact with each other, and potential voltage will be generated when they are separated by a small distance. The TENGs are small in size, lightweight, and easy to make with the facile materials in our daily lives. They are suitable for various application scenarios. However, since the amount of electricity and energy density generated by TENGs is small and low, the TENGs could only be used for some low-power electronic devices. Therefore, it would better integrate the TENGs with conventional EMGs or PZGs together to realize sustainable energy harvesting for self-powered wireless sensing devices in sustainable agriculture.

TEGs could harvest sustainable heat energy in agriculture systems with the Seebeck effect. The electricity is generated inside two different thermoelectric materials under a temperature gradient. The electrons would move from the low-temperature region to the high-temperature region to form the potential difference when the temperature gradient existed at both ends of the thermoelectric materials. The semiconductor thermoelectric materials such as the traditional P-type semiconductors and N-type semiconductors have strong thermoelectric potential differences. However, the TEGs can not be widely applied in actual situations since it has a poor insulation effect, low output power, high material cost, and low conversion efficiency.

MFCs could directly convert chemical energy in organic matter into electrical energy by microbes. There are many microbes in agriculture systems such as the soils in planting. There, the plant MFCs (PMFCs) are developed by the metabolism of microbes in the plant roots with photosynthesis. The MFCs have low power generation efficiency, so they can only be applied to small electronic devices. But they are environmentally friendly, sustainable, low-cost, and pollution-free to the environment. It would be of great significance to promote the development of sustainable agriculture by making full use of the microbes in agriculture environments, not only for the self-powered wireless sensing devices, but also for sustainable agriculture production.

How to choose the self-powered technologies in actual agriculture systems would be determined by sustainable energy. Self-powered technologies are always developing with advanced information technologies such as artificial intelligence, and new materials. It may integrate multiple generators together to harvest sustainable energy so that it can achieve stable, continuous, and uninterrupted energy harvesting in actual sustainable agriculture systems.

4. Self-Powered Wireless Sensing Network

Self-powered wireless sensing networks could be made up of self-powered wireless sensing devices, a wireless transmission network, a cloud center, and the users. Self-powered wireless sensing devices are deployed in actual situations of the planting, breeding, and food supply chain with the sustainable energy harvested. The devices are responsible for acquiring the sensor data and transmitting the sensor data to the cloud center by the wireless transmission network such as the general packet radio service (GPRS) or 3G, 4G, or 5G mobile communication technology networks. The cloud center could manage all the monitoring data with models such as the AI models of machine learning, artificial neural network (ANN), and convolutional neural network (CNN), store them in the database, and display them with the website in the server. Users such as farmers, enterprise managers, or consumers could master all the information in real time through this self-powered wireless sensing network.

Many advanced technologies such as flexible electronics, wireless sensing, energy harvesting, edge computing, AI, and sustainable and biocompatible materials have been developed. The self-powered wireless sensing network would have a great promotion in terms of functionality and practical application adaptability for agricultural biology. Agricultural sustainability would also be improved with sustainable energy harvesting, smart precise production efficiency increase, and carbon emissions reduction by the self-powered wireless sensing network.

5. Practical Implementation

To realize the SAS in actual agricultural situations, sustainable energy harvesting, self-powered wireless sensing, and smart models are the main things that need to be addressed and solved. Many parameters in planting, breeding, and the food supply chain need to be monitored and sensed to master the production status. These parameters may be environmental, crops, animals, and fresh foods. The more comprehensive the acquired parameters, the more beneficial it is for production management and efficiency improvement. Self-powered wireless sensing could provide the opportunity for acquiring the agricultural parameters with a significant amount of carbon emissions reduction by harvesting sustainable energy in actual agricultural systems. However, the big challenges that exist are how to continuously improve sustainable energy harvesting efficiency for power the wireless sensing devices and how to improve the accuracy of the wireless sensing in different sensing parameters. This may be solved with the development of the self-powered technology of solar cells, EMGs, TEGs, PZGs, TENGs, MFCs, or other future new generators, and the wireless sensing technologies that are smart, flexible, biocompatible, and more.

It is not enough to monitor the actual complex agricultural parameters in real time. Smart decisions should be made based on the big wireless sensing data to improve agricultural production precision and efficiency. The smart models between the big sensing data and the agricultural production would be necessary and important. The smart models include the models of sensing data with planting, breeding, and food quality in the supply chain. There are many models that now exist in actual agricultural monitoring such as the CNN or deep learning for image reorganization, machine learning for sensing data with crops or animal growth, and the ANN for food quality. However, the sensing data are so large that the computing ability should be enhanced by the hardware support with powerful computing power. This would add to the hardware cost. Edge computing may be applied to reduce the load for computing since it could be integrated with wireless sensing devices on the spot. Another challenge that existed was how to improve the accuracy of the smart models since large samples were required for training. It means that the long-term sensing data should be acquired and the biology parameters should be also measured to build the models, which would be good for complex agricultural systems. This would depend on the long-term monitoring and the models continuously training, calculating, and verifying.

In addition, how to improve agricultural sustainability further after the SAS practical implementation would also be a big challenge since the complex agricultural systems not only need smart wireless sensing and monitoring, but also need sustainable production for our daily environments and food quality. This challenge could be addressed by integrating sustainable energy harvesting, self-powered wireless sensing, and smart models with AI together in different processes of planting, breeding, and the food supply chain to implement real sustainable agriculture systems and enhance the food quality and human health.

6. Conclusions

Agricultural systems are complex with the planting, breeding, and food supply chain, and many sustainable natural renewable and recycled facility energy such as light, wind, water, heat, acoustic, RF, and microbe. Self-powered technologies could effectively harvest the sustainable energy that existed in the agricultural environment to realize self-powered wireless sensing, reduce the agricultural environment's carbon emissions, and, finally, improve agricultural production’s transparency, efficiency, and green sustainability. With the development of advanced sustainable energy harvesting, self-powered technologies, flexible and biocompatible wireless sensing, AI, and biotechnologies, self-powered wireless sensing would be of great significance for providing actual applications in smart and sustainable agriculture. This perspective suggests that a self-powered wireless sensing system would be expected to be an effective way to realize the improvement of smart agriculture production efficiency while achieving green and sustainable agriculture, and, finally, ensuring food quality and safety and human health in the future.