Emmanuel Abiodun Abioye

This paper discusses the prospect of utilization of solar energy for aquaponics operation. Aquaponic is a platform for farmers to simultaneously grow fish and plants in a same unit. It is sustainable and produces little waste. The need of pumps for continuous water recirculation and air supply within the system could be a hindrance in the aquaponics operation especially if the unit is nowhere near any power outlet. It is indeed a visible solution as Malaysia located at equator and receives average sunlight ~9 hours a day throughout the year with solar intensity as high as 1800-1900 kWh/m2. The work presents detail equipment for establishment of suitable solar PV system for aquaponics operation and reviews utilities of aquaponics platform that can be supported using solar energy. Possible integration of Internet-of-Things (IoT) for remote monitoring of such solar operated aquaponics unit is also discussed. Analysis showed that even when operated with full energy supply for only 12 hours, the yield and growth rates of the crop and fish grown in the system powered remains unaffected. This signified the potential for the use of solar energy as alternative energy for operation of the aquaponics unit. The main advantage perhaps is the realization of aquaponics setup in remote area where electricity is not accessible. Installation cost may be relatively high (100W PV system could cost nearly RM 600 for installation) but for a long run, it is highly beneficial as utility cost and cost for installing the national grid can be significantly reduced. Summarizing, the project introduced the concept of smart farming via aquaponics for a sustainable production of crop and fish using a renewable and clean solar energy for its operation.

Freshwater is essential for irrigation and the supply of nutrients for plant growth, in order to compensate for the inadequacies of rainfall. Agricultural activities utilize around 70% of the available freshwater. This underscores the importance of responsible management, using smart agricultural water technologies. The focus of this paper is to investigate research regarding the integration of different machine learning models that can provide optimal irrigation decision management. This article reviews the research trend and applicability of machine learning techniques, as well as the deployment of developed machine learning models for use by farmers toward sustainable irrigation management. It further discusses how digital farming solutions, such as mobile and web frameworks, can enable the management of smart irrigation processes, with the aim of reducing the stress faced by farmers and researchers due to the opportunity for remote monitoring and control. The challenges, as well as the future direction of research, are also discussed.

The demand for freshwater and food is on the increase due to the rapid growth in the world’s population, while the effect of global warming and climate change poses a severe threat on water use and food security. Conventional irrigation system suffers due to an inefficient management of water and energy, while insufficient supply of water to plant increases their stress which often affects its growth and development. Hence, there is a need to increase research focus on water use efficiency in irrigation agriculture. This paper is aimed at investigating the performance of smart drip and subsurface fibrous capillary irrigation experiment for the cultivation of cantaloupe plant to increase the yield and quality of fruit while decreasing the water and energy usage. To achieve enhancement of subsurface fibrous capillary and drip irrigation system, an Internet of Things (IoT) approach was used to improve monitoring of soil, weather, plant and control of water application. The performance comparisons of both methods was evaluated in terms of water-saving in greenhouse cultivation experiment. The results obtained, shows that the smart fibrous capillary irrigation has water use efficiency of 19 g/Litre with average fruit sweetness of13.5 Brix. While, drip irrigation has 4.85 g/Litre and average sweetness of 10 Brix on the harvested fruit after 90 days of cantaloupe plant cultivation experiment. These have shown that precision irrigation through enhanced smart fibrous capillary irrigation can be used to achieve high water-saving and a good quality yield. It is expected that the research output will help to improve water-saving agriculture towards achieving food security.Keywords: Water Saving; Capillary Irrigation; Drip Irrigation; Internet of Things; Water Use Efficiency

Electricity theft has caused huge losses over the globe and the trend of its perpetuation constantly evolve even as smart technologies such as smart meters are being deployed. Although the smart meters have come under some attacks, they provide sufficient data which can be analysed by an intelligent strategy for effective monitoring and detection of compromised situations. So many techniques have been employed but satisfactory result is yet to be obtained for a real-time detection of this electrical fraud. This work suggests a framework based on Universal Anomaly Detection (UAD) utilizing Lempel-Ziv universal compression algorithm, aimed at achieving a real-time detection in a smart grid environment. A number of the network parameters can be monitored to detect anomalies, but this framework monitors the energy consumption data, rate of change of the energy consumption data, its date stamp and time signatures. To classify the data based on normal and abnormal behaviour, Lempel-Ziv algorithm is used to assign probability of occurrence to the compressed data of the monitored parameters. This framework can learn normal behaviours of smart meter data and give alerts during any detected anomaly based on deviation from this probability. A forced aggressivemeasure is also suggested in the framework as means of applying fines to fraudulent customers.