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ABSTRACT

The Internet of things and artificial intelligence are emerging technologies that collect and analyze data from smart sensors to satellites, using cloud-based analytic software tools to increase the long-term viability of aquaculture operations, efficient, and even environment friendly. With the benefits of modern technologies, it encourages well-organized resource use,   minimizes human labours in many aspects.  The internet of things is at the base of intelligent aquaculture, while big data collecting and research will aid in the development of artificial intelligence technology for aquaculture. Innovative monitoring equipment is now possible because of technological and digital advancements, allowing for better fish stock management. Big data, the internet of things, sensors, robots, data storage, artificial intelligence, and transmission will all become more efficient and affordable, increasing their utilization. This article offers a brief summary of aquaculture`s usage of the internet of things and artificial intelligence.

Keywords: Internet of things, artificial intelligence, sensors, eco-friendly, cloud-based, robotics

 

Cite this article as : Wanjari, RN., Ramteke, KK.,  and Dhanalakshmi M (2021). Importance of Internet of Things (IoT) and Artificial Intelligent (AI) in Aquaculture. Food and Scientific Reports. 2 (12): 16-21

For hundreds of millions of people around the world, the aquaculture sector provides a significant source of income and livelihood, and it is also a vital source of food and nutrition. “Food and Agriculture Organizations estimated 52% of global fish stocks such as fully exploited, 28% overexploited or depleted, 20% moderately exploited, and only 1% showing marks of recovery as a result of the consequences of fishing since 1970” (FAO, 2009). In the last 50 years, global aquaculture production has increased significantly. Around the world, the aquaculture business has experienced tremendous expansion. One of the most important reasons is that fish farming is one of the best lucrative businesses (Ullah & Kim, 2018). Aquaculture commands increasing attention worldwide. Aquaculture has been the world`s fastest-growing food industry in current years, with annual growth of 10% compared to 2–3% for other major food sectors. Aquaculture has grown considerably importance over the last two decades and is now a major economic activity all around the world. Total world fish production reached 178.5 mmt (FAO, 2018), among the total production aquaculture contributing 82.1 mmt (46%). The total world aquaculture production inland contributing 51.3 mmt and marine 30.8 mmt. The proportion of aquaculture production between continents is highly skewed, with Asia accounting for 91% of total production. Total fish production in India is 14.2 mmt, with 3.72 mmt of marine fish production and 10.48 mmt of inland fish production (Handbook on Fisheries Statistics, 2020). Aquaculture is a speedily growing fisheries sector in India with an annual development rate of over 7%. Marine environment monitoring has fascinated more and more consideration due to the rising concern about climate change. Advanced information and communication technologies have been utilised to the creation of innovative marine environment monitoring systems throughout the last few decades. The internet of things (IoT), for example, has played a significant role in this sector. Due to the growing load of contaminants by several methods such as discharge of industrial waste, dumping of untreated urban waste, old electrical equipment, scrapping of shipwrecks, agricultural runoff, residues of persistent organic impurities, oil spills, contamination of the marine environment has become a key issue worldwide (Sarkar, 2006, Sarkar et al., 2021). Conventional farming models sometimes need cheap capital investment and low labour skill requirements, making them undesirable to young people due to low money returns. Furthermore, traditional models can put a strain on limited land and other resources, and they are more subject to natural disasters like climate change, flooding, and drought, among several other things. With advancements in monitoring and automation technology in recent years, aquaculture research has resulted in the development of production technologies that have improved the quality of fish farming in ponds, as well as the sustainable use of resources, resulting in enhanced and increased fish production. With the development of novel technologies, aquaculture has changed from traditional labour-intensive farming toward mechanized aquaculture and progressively to automated systems. The labour-intensive model mainly relies on human experience, with high labour cost. With declining labour availability for aquaculture and growing demand for aquaculture products, there is a crucial need for a new intelligent aquaculture model. Internet of things (IoT), artificial intelligence (AI), 5G, cloud computing, robotics, equipment, big data, through a remote regulator or robot autonomous control of aquaculture facilities, and machinery to comprehensive all production and management operations make bright aquaculture possible. It comprises the integration of current information technology with the entire aquaculture production, operation, management, and service industrial chain. It`s a new type of modern aquaculture development enterprise. Furthermore, big data and artificial intelligence are at the foundation of IoT`s intelligent operation, which is essential for aquaculture management effectiveness. Intelligent equipment obsessed by the internet of things is the base of intelligent aquaculture, which could resolve labour force limitations and mitigate environment friendly resource problems in aquaculture. However, the automated production approach involves more skillful workers, which affects on cost-effectiveness (Engle et al., 2020). An IoT-based automation structure can regularly and ably monitor various critical parameters in fish farming, such as the dissolved oxygen, temperature, and water level (Gao et al., 2019). Monitoring of marine and freshwater environments has received a lot of attention in recent decades. Governments and educational programs have made substantial improvements in this area`s research and development. Various marine environment monitoring technologies and systems have been developed using advanced information and communication technology. In May (2019), the Indian Government formed the Ministry of Fisheries, Animal Husbandry, and Dairy. By increasing India`s fisheries and aquaculture, the Indian government is working toward another "blue revolution”. The future development of aquaculture, according to the National Fisheries Development Board (NFDB), is dependent on the deployment of unique and modern advanced production technologies, the management and utilization of underutilized water resources, and proper market linkages.  For achieving  the  blue revolution  (Neel  Kranti  Mission)  and  making  fisheries  a  modern world-class industry, the need is to embrace new technologies like sensors, robotics, blockchain, AI, IoT, etc.  These technologies can play an important role in ushering the blue revolution. Amongst the new technologies, the IoT and AI are important for the daily basic devices that are used in day to days in our lives.  The IoT is about involving everyday things implanted with electronics, sensors, and software to the internet supporting them to collect and interchange data (Cisco, 2019). By 2025 it is expected that 75.44 billion devices will be part of IoT, Statista (2019). There is a high potential for IoT in fisheries and aquaculture and fishers/farmers can have an edge in a competitive market.  In India`s 2020 budget tax benefits have been announced for startups in AI, deep technologies, ML, and big data. The main aim to exploit the potential of internet of things (IoT) is to contribute to the development of sustainable and resilient aquaculture systems that ensures profitability, maintain healthy aquatic ecosystems, and strengthens capacity for adaptation to climate change. Conventional marine and freshwater environment monitoring systems such as continuous monitoring of water quality parameters, oceanographic and hydrographic research vessels are very expensive as well as time-consuming. Wireless sensor networks (WSNs) eventually led to the internet of things (IoT). IoT offers far stronger data processing capabilities than WSNs, allowing intelligent object control. The intelligent aerator system, for example, may precisely manage the aerator, the cleaning equipment based on water quality, the circulating water treatment equipment, fish behaviour, and climatic data to enable exact water quality control. Based on biomass, water quality, surroundings, and behaviour of the fish, the intelligent feeder and deep learning can feed the fish in an appropriate and timely manner. The fish will continue growing and healthy as a result of this. The automatic fish separator can collect fry of various sizes and ages and pool them all together. The condition monitoring and early warning system are intended to ensure that the circulating water system operates safely at all times. Internet of things and artificial intelligence in fisheries not only helps in farm management but even in open sea fishing by tracking the global fishing activity through the combination of satellite data. Fish consumption worldwide has increased four folds in the past decade. Aquaculture has become a field with increasing demand and reduced productivity. Artificial intelligence-based technology can be a key to achieve higher production with less manpower.

 

Historic background

                  “IoT was first recommended by the Auto-ID Center an association between multiple universities and Massachusetts Institute of Technology” (Sanjay et al., 2015). Their concept was to apply a low-cost radio frequency identification tag (RFID) to each object or item, which would then be connected to a global network to create a uniform standard for both identifying things and sharing data. The Auto-ID Center was separated into two groups in 2003: EPC global and Auto-ID labs. EPC Global is a division of GSI, which created the standards in this case, and Auto-ID Labs, which is still made up of several of the original universities and is focusing on IoT infrastructure development (Cambridge Auto-ID Lab, 2015).

Internet of things (IoT) and artificial intelligence (AI) characteristics

·   Information is collected using a variety of temperature and humidity sensors, CO2 sensors, light sensors, dissolved oxygen sensors, and other water quality sensors, as well as cameras and additional digital image data acquisition equipment.

·   Transmitting the composed data to the control center over communication nodes. This information may contain the growth of fish, operation, environmental parameters, and resource allocation.

·   Data processing, handling, and decision-making are achieved in the cloud platform.

·   To achieve sustained high efficiency, high quality, ecological, health, and intelligence aquaculture, decisions are feedback to each execution equipment, and operations are carried out intelligently and automatically.

Attributes of IoT and AI in aquaculture

Data Analysis

                  The rapid development and adoption of IoT technologies in marine environment monitoring have resulted in massive amounts of data, which can now be analysed due to recent advances in big data analytics. Dealing with marine environment data, like many other IoT-based data gathering systems, presents some substantial issues, mainly the vast amount of data and significant poor data. Researchers from all across the world have been attempting to address these issues.

 In Marine and Freshwater Environment Monitoring

                  In marine environment includes monitoring of Ocean sensing and regular monitoring, waves and currents, water quality, coral reef monitoring, seaweed, seagrasses resources, etc. Since these, all resources are fragile. A marine fish farm monitoring system keeps track of water quality and conditions, such as temperature and pH, as well as the amount of faeces and uneaten feed in a fish farm, as well as fish health and activity, such as the number of dead fish. A wave and current monitoring system monitor waves and currents for safe and secure passage through waterways. Coral reefs are diverse underwater habitats bonded by calcium carbonate structures secreted by corals. Shallow coral reefs, also known as "sea rainforests," are home to the most diverse ecosystems. Threats of Coral Reefs include natural disasters, sedimentation, coral bleaching, destructive fishing, etc. Seagrasses are underwater flowering plants that grow in meadows in brackish or marine waters along the beach in temperate and tropical climates. Sea grass beds are subject to anthropogenic pressure in a variety of ways. “Thermal effluents, toxic agents, industrial discharges, cultural eutrophication, dredging, commercial fishing, oil spills, and changes in light transmission due to turbidity and color, have been associated with such reductions in seagrasses biodiversity”. In order to proper monitoring of such resources, IoT and AI are played important roles. In freshwater environment includes monitoring of aquaculture ponds, aquatic plants, water quality parameters, etc. A water quality monitoring system usually contains pH, turbidity, temperature, dissolved oxygen (DO) and conductivity, in rivers, lakes, reservoirs, and other water bodies. The IoT smart monitoring system includes multiple sensors that detect the environment, and the fish pond manager can make key decisions based on the readings from these sensors to improve the quality and quantity of fish output.

IoT and AI in open sea fisheries/ Marine fish stock management

                  The majority of fish that we consume comes from open sea fishing. Due to increasing population and demand, overfishing and poaching have increased within a short time. Illegal, unregulated, unreported (IUU) fishing has increased to a great extent. IUU fishing accounts for 15 to 30 percent of global yearly catches, according to the UN Food and Agricultural Organization (FAO) and academic research, though the level of damage to fisheries varies substantially by region and species. Illegal, Unreported, and Unregulated (IUU) fishing affects almost 85 percent of global fish populations. Indian IUU in surplus of one million tonnes per year. Derelict fishing gear is occasionally referred to as "ghost gear is whichever abandoned, lost or otherwise discarded fishing gear (ALDFG) in the marine environment”. Ghost fishing is frequently due to passive gears like traps, gillnets, trammel nets, and tangle nets. Traditionally to stop this, some organisations have hired observers at high costs in order to monitor fishing activities on ships. But in locations like arctic, the climate and area made it difficult for observers to track IUU vessels. AI plays a great role in these areas. Through satellite and AI programs, fishing vessels can be observed by image recognition and automatic review of video footage. This will help to reduce IUU fishing and restore the wild population. It is estimated that 640,000 tonnes of fishing gear are misplaced or lost in the oceans each year (FAO, 2018).

Conservation of Endangered Fishes

                  Many conservation efforts are made and yet open sea makes it difficult for humans to monitor them. Through vision sensors and cameras, AI drones can track endangered fishes and analyze their habitat much faster than humans. Many indigenous fish species in India are in danger of extinction, despite living in a relatively inaccessible habitat. More than a dozen species of Chondrichthyes fishes are categorised as endangered in India, according to the most recent IUCN red data list. Platanista gangetica (Ganges River dolphins) occur in the Ganges-Brahmaputra River system predominantly in India and Bangladesh. They are listed as Endangered by the IUCN due to a probable population decline of at least 50 percent over the last 50 years and anticipated future population declines. With the help of drones, we can able to easily track fish, whales, dolphins, etc. by setting up transmitters on their fins. This helps in studying the behaviour of the organism much easier and conserves the better aquatic resources.

Predicting Environmental Changes

                  Shrimps, oysters, and corals, among particular, make it increasingly difficult to calcify their shells when the ocean temperature and pH rise. Calcium shells are found in a variety of important species, including zooplankton, which is the foundation of the marine food chain. The entire marine food web is changing, which might lead to "food chain cracks." As a result, the worldwide fish population is shifting in terms of distribution, productivity, and species composition, resulting in complex and interrelated effects on seas, estuaries, and sea grass beds, which offer habitat and nursery grounds for fish. Because of their bioclimatic niche, pelagic fish stocks have distinct geographical and temporal distribution patterns. Climate change and the resulting changes in primary and secondary production have an impact on the distribution ranges, migratory patterns, and stock size of many marine fish species. The straddling pelagic stocks, including as herring, mackerel, capelin, blue whiting, sprat, anchovy, and sardine, are the most severely impacted. With the help of sensors are used to capture a variety of vital climate information, including salinity, water temperature and depth, barometric pressure, and sea-tide height. The data is sent to a Microsoft-based cloud platform, where AI and other analytical tools transform it into a visualised form with weather predictions for the location.

IoT and AI in feeding devices

                  Feed accounting for approximately 60% of the entire cost of an aquaculture system. Too little or too high feeding can cause several issues in the containment. To avoid wasting money on overfeeding, it employs sensors and machine learning to detect and identify when fish are ready to eat. Feeding less, on one hand, can decrease muscle conversion and in extreme cases (in shrimps) it can lead to cannibalism and mutual attack. Excess feeding, on the other hand, will result in feed wastage and depletes the water quality. Appetite measurement can improve in providing the correct amount of feed at the correct time. Through vibration-based sensors and acoustic inputs, AI plays a significant part in reading the fish. This will help in differentiating a hungry fish from that of a full. An Indonesian aquaculture intelligence company known as ‘eFishery` has recently developed an AI feed dispenser that releases the right amount of feed at the right time.

 Fish seed screening and counting

                  Identification and selection of healthy fish seeds are very important in fish farming. Often it becomes laborious and needs to employ many workers for screening of healthy fish seed. XperCount is an IoT-enabled device that uses AI and computer vision to count and size organisms like shrimp and fish larvae. It connects to a portal where consumers may access data and analytics.

Regularly monitoring of stocks

                  Vision-based sensors on AI devices make it possible to analyze the swimming pattern, size, injuries, etc on the cultured animal. These data are preserved in order for comparison in the future for the sustainable use of aquatic resources. The greatest threat to aquaculture is the outbreak of diseases. AI programs can detect disease outbreaks before they happen by comparing programmed data with the collected data from the site. They are even capable of applying preventive measures. This reduced fish mortality and minimised dependency on more expensive treatments.

Protection of marine and freshwater environment

                  Environmental protection is currently one of the most pressing challenges facing the planet. The ultimate purpose of ocean monitoring is to safeguard the marine ecosystem. The majority of today`s marine environment monitoring programs collect and analyse vast amounts of data from the ocean, but no action on protection regulations has yet been taken. With the growth and sophistication of IoT and big data technologies, as well as their wide range of applications in marine environment monitoring and protection. Massive data obtained from marine environments will be analysed using advanced big data analytics, and the findings will be sent to the appropriate marine environment management department, agencies/control centers for quick decision making and manual in real-time interventions to help defend the marine environment from disasters such as oil spills, high tides, waves, etc.).

Applications in Smartphone

                  AI Smartphone applications can help prominently in helping farmers for testing water quality and predicting diseases. “IoT applications are available in every industry for   Smart   Homes, Connected Cars, Wearables, Smart  Cities,  Poultry and   Farming, Agriculture,  Smart  Retail, Smart grids, Industrial  Internet,  and  Healthcare” (IoT Analytics, 2018).  Through these applications, farmers can prevent diseases even before the outbreak starts. Farmers and developers input photographs of shrimp illnesses, parasites, and other pests into the app on a regular basis. The software can learn about the diseases and save them for future use by using these photographs.

IoT and AI in the fish processing sector

                  Fisheries and aquaculture products are key sources of protein, nourishing and supporting hundreds of millions of people around the world. Aquaculture contributed 52% towards global food fish consumption and it is expected to reach 59% by 2030. Processed seafood always has a higher demand. Fish and shrimp processing facilities have developed to a level where automated robots do the work more accurately with less time thus, increasing the production by several folds. Cutting, filleting, or cleaning the products can be done through programmed artificial intelligence robots with much accuracy towards size, shape, and proper hygiene. Quality control and grading can be done through AI programs equipped with visual image sensors and cameras. After grading, the processed foods can even be packed and transported through AI robots.

Internet of Things (IoT) and artificial intelligence (AI) benefits and drawbacks

Benefits

·   The internet of things and artificial intelligence have the potential to reduce trash discharge, recycle waste, and optimise resource usage. That example, through big-data analysis and real-time modifications, can minimise feed consumption and improve waste and water quality control.

·   Intelligent aquaculture can significantly improve the productivity, quality, and security of aquatic goods while also significantly lowering their production and operation costs. The health of the ecosystem and fish can be constantly monitored with the use of real-time monitoring and management. It can keep the fish in the best possible condition for growth and improve the fish`s quality.

·   Effective climate and aquaculture environmental data management can assist boost aquaculture volumes while lowering losses. This is advantageous for addressing the issue of seafood demand while also protecting wild resources.

·   Robotics and intelligent equipment can help free up labour and increase manufacturing efficiency.

·   AI and IoT help to manage aquaculture in a much efficient way and maintains high accuracy in the prediction of disasters (disease outbreak or depletion of water quality).

 

Drawbacks

·   Automated production mode requires more skilled workers

·   AI and IoT are much costly and many can`t afford them.

·   Maintenance of AI and IoT systems has high cost too.

·   New technologies may creates unemployment for the labourers.

·   Globally, around 59.6 million people rely on fisheries and aquaculture as their prime source of livelihood. This could end up the fisherman employment.

·   Because aquaculture is such a high-risk business, a sensor or other component failure might result in a catastrophic error and a significant financial loss.

 

Conclusions

                  Fish farming is the fastest in the world food sector, but as our early-stage start-ups reveal, the industry is still trying to catch up in terms of innovation. It`s important to note that most IoT solutions include some form of artificial intelligence, such as computer vision for species monitoring or machine learning for analytics and predictive modelling. IoT and AI in aquaculture can advance sustainability and efficiency of resource exploitation in various aspects. It can also reduce labour cost, increase the quality of aquatic products and improve productivity. Other problems, such as high capital and energy costs, should, however, be addressed to develop intelligent aquaculture. The Internet of Things and Artificial Intelligence technology platform, which incorporates digitization, industrialisation, automation, and big data information, could aid ecosystem-based fisheries management and aquatic resource sustainability. To achieve automatic aquaculture production, information, and sustainable management, IoT and AI technologies are expected to assemble traditional aquaculture with current intelligent expertise, breeding technology as well as information technology.

 

References

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