Authors: Ahmad Nizar Harun, Robiah Ahmad, Norliza Mohamed, Abd Rahman Abdul Rahim and Hazilah Mad Kaidi
Abstract: Advanced technology in agriculture has enabled the manipulation of the artificial light spectrum in plant development such as improving yield and plant growth. Light manipulation using light-emitting diodes or LEDs can inhibit, delay, or even promote flowering. Some studies have shown that far-red (FR) light can stop flowering, but studies have not fully explored the best method involving intensity and duration to induce plant growth. This paper presents results on LED light manipulation techniques, particularly FR light, on plant flowering control and plant elongation. The light manipulation technique on the combination of colors, photoperiods, and intensities proved that it can stop flowering, and stimulate and control the growth of plants during cultivation. The system was monitored using an Internet-of-Things (IoT) remote monitoring system, and it performed data mining. The results showed that plants that were grown under artificial sunlight (T5) and normal light (T1) treatments were superior compared to others. The FR light delayed flowering until 50 days of planting and accelerated the plant growth and increased the fresh weight by 126%. The experiment showed that a high variable intensity at 300 μmol m−1s−1 showed a great performance and produced the largest leaf area of 1517.0 cm2 and the highest fresh weight of 492.92 g. This study provides new insights to the researchers and the farming community on artificial light systems in improving plant factory production efficiency and in determining the best plant cultivation approach to create a stronger indoor farming management plant.
Keywords: artificial light; controlled-environment agriculture (CEA); light spectrum; variable light intensities
Authors: Yasaman Memari, Ashkan Memari, Sadoullah Ebrahimnejad, Robiah Ahmad
Abstract
Carbon trading is a market-based mechanism for controlling carbon emissions by providing economic incentives to reduce emissions. In recent years, there has been an increasing interest in modeling supply chain networks under this scheme; however, to date, only a limited number of researchers have investigated the implication of this mechanism for biofuel supply chains. The optimization model presented in this paper examines a trade-off between the cost of trading carbon credits and costs associated with outsourcing of the biomass pretreatment process when carbon emissions exceed the predetermined carbon cap in a biofuel supply chain. To demonstrate the applicability of the model, we analyzed challenges in supplying different sources of biomass to two biorefinery plants and shipping the produced biofuels to multiple demand zones. The results showed that carbon emission reductions have a relatively nonlinear pattern when the carbon credit price increases linearly. Furthermore, we presented significant managerial and policy insights on the impact of different carbon emission caps on total costs and total emissions. Moreover, we analyzed the cost adjustment between trading carbon credits and outsourcing decisions for different carbon cap settings. This paper ends with suggestions for further development of the presented model for future researches.
Keywords Biofuel supply chain . Carbon trading policy . Optimization . Outsourcing . Logistics
Authors: Syaidathul Amaleena Rossli, Robiah Ahmad, Sathiabama T. Thirugnana
Abstract
Load forecasting plays a substantial role in designing a power harvesting system. All manufacturing plants are highly dependent on the primary grid as their main power supply. Manufacturing plant consumes high electricity due to its nature that requires the plant to operate 24 hours a day. This study explores the potential of solar harvesting system for high grid consumer, and it is conducted to investigate the possibility for manufacturing plant X to rely on the renewable energy as an alternative power supply. Based on the demand of power that may vary during on-peak and off-peak in conjunction with business planning, a forecasting model has been developed to predict the plant’s demand. Based on the model developed, an optimal design of the PV harvesting system for the manufacturing plant is proposed using Hybrid Optimization of Electrical Renewable (HOMER) software with respect to economic aspect. The designed system managed to supply 88.2% of the demand meanwhile 11.2% were supplied by the main grid. However, the cost is intolerable with calculated operating and maintaining the system is RM14.7M (USD 3.57M)per month as compared to current cost which is significantly less. Further research on hybrid renewable energy harvesting may be conducted that may improve the proposed system.
Keywords
ARIMA model; Energy forecasting; Manufacturing plant; Renewable energy; Solar harvesting
Authors: MOHD ISMIFAIZUL MOHD ISMAIL, RUDZIDATUL AKMAM DZIYAUDDIN, ROBIAH AHMAD, NORULHUSNA AHMAD, NOOR AZURATI AHMAD AND AFIFAH MAHERAN ABDUL HAMID
ABSTRACT The localisation and positioning in Wireless Sensor Node (WSN) are prone to tracking loss because of battery depletion resulted from high power consumption. Considering this, Energy Harvest- ing (EH) is a significant factor to ensure the sustainability of WSN trackers. Therefore, the key objective of the paper is to review the existing EH approaches, specifically for WSN trackers. An overview of WSNs including the underlying wireless communication technologies is initially presented. We compared the communication range, data rates, power consumption and also the cost across wireless technologies used for WSN. This paper further discussed the localisation and positioning techniques using the Global Positioning System (GPS) and other types of sensors exploiting signal parameters like Received Signal Strength Indicator (RSSI) and Angle of Arrival (AoA). Subsequently, we reviewed the energy harvesting approaches in terms of power density, efficiency and also highlighted their advantages and disadvantages. The EH components such as energy storage and energy-combining circuit for active monitoring are presented as well. Finally, this paper outlined the key challenges and future regards EH for WSN.
INDEX TERMS Energy harvesting, piezoelectric, solar, hybrid energy, boost converter, GPS tracker device.
Authors: Muhammad Saqib Iqbal, Zulhasni Bin Abdul Rahim, Syed Aamer Hussain, Norulhusna Ahmad, Hazilah Mad Kaidi, Robiah Ahmad, Rudzidatul Akmam Dziyauddin
Abstract: The use of mobile communication is growing radically with every passing year. The new reality is the fifth generation (5G) of mobile communication technology. 5G requires expensive infrastructural adjustment and upgradation. Currently, Pakistan has one of the most significant numbers of biometrically verified mobile users. However, at the same time, the country lags incredibly in the field of mobile internet adoption, with just half of the mobile device owners avail broadband subscription. It is a viable market with a large segment yet to be tapped. With the advancing progression in Pakistan towards the internet of things (IoT) connectivity, i.e., solar-powered home solutions, smart city projects, and on-board diagnostics (OBD), the urgency for speed, bandwidth and reliability are on the rise. In this paper, Pakistan’s prevalent mobile communication networks, i.e., second, third and fourth generation (2G, 3G and 4G), were analyzed and examined in light of the country’s demographics and challenges. The future of 5G in Pakistan was also discussed. The study revealed that non-infrastructural barriers influence the low adoption rate, which is the main reason behind the spectrum utilization gap, i.e., the use of 3G, and the 4G spectrum is minimal.