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Water scarcity is one of the biggest issues affecting the country’s agricultural economy. In order reduce the effort, put by a farmer to collect water and to avoid unnecessary water consumption, we propose a farmer-centric irrigation support system for effective water management and suggest methods to improve the yield. Sensors such as temperature sensor, soil moisture sensor, and pH sensor are deployed to monitor soil parameters and ambient temperature. The GSM module provides communication between the farmer and the field. The status of the field can be monitored through mobile application and notified via SMS. Weather APIs are integrated to get information on rain, and based on this, irrigation can be postponed if there is a chance of rain in the coming days. Override option is also provided for manual operation of water pumps. This paper presents the architecture and algorithm of the proposed farmer-centric smart irrigation system.

This paper provides a comprehensive review of literature on the properties of sugar industry waste, their varied uses in energy and construction sector, performance and limitations. An efficient upcycling of sugar industry waste in energy production would help the energy sector to reduce its dependency on non-renewable fossil fuels. Literature demonstrates that in the recent years there has been an increased research interest in thermochemical conversion of sugarcane bagasse to produce cleaner energy, rather than its landfilling or combustion. On the other hand, utilisation of secondary by-products from sugar industry in the production of cement, bricks, paver blocks, activated binder and other construction products helps to cut down the carbon footprint of the construction industry, while improving the properties of the final products. From the perspective of the sugar industry, such an arrangement eliminates disposal problems and creates additional revenue. Although independent research studies investigating the use of sugar industry by-products exist, few studies consider these valorisation options together to minimise waste and to create an efficient material flow chain. This study identifies various material and energy recovery pathways from published literature and connects the materials and processes to form a continuous material supply chain with minimum wastage. From the findings, a symbiotic framework has been developed with primary and secondary by-products from the sugar industry serving as source materials for energy production and sustainable construction products.

As the number of COVID-19 cases keeps growing exponentially in the world, the use of the combination of wearable technology and IoT technologies opens up a wide variety of possibilities. An IoT-enabled healthcare device is useful for proper monitoring of COVID-19 patients to increase safety and reduce spreading. The healthcare device is connected to a large cloud network to obtain desirable solutions for predicting diseases at an early stage. This paper presents the design of a healthcare system that makes use of these technologies in a cost-effective and intuitive way which highlights the application of these technologies in the battle against the pandemic. The wearable can give real-time analysis reports of body vitals so that necessary precautions can be taken in case of infection. The wearable is designed in such a way that it can be used as a precautionary measure for people who are not infected with the virus and as a monitoring device for affected patients during the curse of their treatment. This low-cost design can not only be used to prevent the community spread of the virus but also for the early prediction of the disease.

Natural disaster in India has become a great challenge in the recent years. Each year the rates have been escalating affecting both the social as well as economic progress of the country. India’s topographic/climatic and socio-economic features make the country most vulnerable to the devastating effects of such calamities. Hence, it is the need of the hour to come with a system capable of long term as well as quick prediction of disaster. This can be useful for early preparedness and developing well-planned mitigation/relief system which can reduce the effects of such disaster and can be also useful in channelizing the finding in a right way during calamities. The proposed system consists of modules for prediction of: Weather pattern, flood, earthquake, landslide, fire and gas leakage. The sensor node deployed at various disaster-prone areas transmits sensor data to a local aggregator that pre-process the data and relays to remote monitoring servers. The remote monitoring platform has algorithms for prediction of disaster as well as suggestions for quick response. Hence, the possibility of disaster can be predicted prior to the onset of these calamities.

There has been an ever growing complexity in design and development of Embedded Systems for various applications. The applications like disaster management in a remote location requires embedded system to perform multiple tasks like data acquisition, processing and wireless transmission. And the complexity increases when it has to be performed in parallel. Multi threading on a RTOS has been one of the widely used technique and it is implemented in software. Alternatively, DMA the hardware way of parallel processing on an ARM based microcontroller is a tedious task. But, the API and HAL provided by some manufacturers reduces the development time and simplifies the implementation.This paper shows the implementation of DMA using API and HAL on an ARM based controller of a PSoC. This demonstrates the idea of parallel processing using DMA controller and microcontroller. The DMA transfers the processed sensor data from source register to the destination register without much microcontroller intervention. So that the microcontroller can allocate its execution time for other tasks.

On the 11th of March 2020, the World Health Organization (WHO) affirmed COVID-19, a pandemic, in response to more than 1,00,000 confirmed cases globally in more than 100 nations and the persistent danger of spreading further. Presently, there’s no remedy or vaccine for COVID-19. The only way to curb its menace is taking precautionary measures, as advised by the health experts. Social distancing, that is maintaining a minimum distance of 1 to 1.5 meter between two individuals, is one of the foremost proactive measures advised by WHO. This paper presents a smart wearable device, Suraksha, that can be worn while travelling outside and will help maintain social distancing. The user will be able to rely on this device’s alerting mechanism without having to constantly worry about their surroundings. It is a simple device which is easy to use and is built using basic electronic components. The device is also capable of integrating with the health applications over Bluetooth and support contact tracing.

Open source platforms like Arduino and Raspberry-Pi boards are an excellent choice for DIY projects and quick prototypes. But, the development environment lacks the debugging feature that a professional developer would prefers to have. Also, unlike SoC the Arduino platform does not support configurable hardware in its IDE. The configurable hardware feature in SoC helps to choose the right hardware design after testing. But, the hardware design using HDL in SoC is relatively complex and takes more time. The PSoC tries to solve this issue with its APIs and GUI based hardware configuration in its tool, it also has a debugger feature to test and debug the design. The selection of ADC resolution depends on the applications and ADC of the PSoC can be reconfigured easily. This makes PSoC a suitable platform to develop a generic data logger, that can cater most of the application with re-configurable ADC. The proposed research work discusses the implementation of data logger on Arduino and PSoC and shows the advantage offered by the PSOC over Arduino. An accelerometer sensor data is fed to the ADC of both the boards, the collected data from both the boards are plotted and compared using the Matlab tool.

With the recent advances and proliferation of the Internet of Things (IoT) devices, there is a huge demand placed on its infrastructure requirements. The amount of data generated by these small low-cost, low-power (LCLP) IoT devices is phenomenal and at the same time due to the devices being low-powered, they cannot be used to perform complex computations and other algorithm implementations. There are also limitations in communication data rates at different stages in a Wireless Sensor Network (WSN), which mainly uses wireless technologies such as Bluetooth, Zigbee, LoRa, etc to achieve low power communication. These technologies come with limited bandwidth and are not very reliable at high data rates. Hence the challenge of handling high amounts of data with low bandwidth communication technologies is one of the main hurdles inefficient LCLP IoT system deployments. To address this problem, we propose a combination of data compression techniques, which will result in reduced data size, without compromising affecting the quality of the data. This paper describes the implementation of a combination of Delta and RLE compression techniques on specific sensor data, particularly those used in our deployment of the World's First Wireless Sensor Network-based System for Early warning and Monitoring of Rainfall induced Landslides in Southern India. The test results show a good compression ratio of 52.67% for 12bit ADC, without compromising on the quality of the data. This has been implemented on a Programmable System-on-a-Chip (PSoC) system and the results presented.

IOT based smart home with cloud analytics are becoming popular, as it helps in analyzing the real time power consumption. Home Automation System [HAS] and remote control system in a smart home opens up many ways to control the loads in a smart home. But, there are a lot of challenges when all these features are combined together to make a low cost smart home system. Often in the design, the HAS and remote controllability can conflict with each other when trying to control the same load. This paper outlines the design of a low cost smart switch that incorporates HAS, remote controllability and IOT cloud platform. It also describes the challenges faced and a possible solution.

Extensive studies have been reported on the development of service-life prediction of reinforced concrete structures in the last two decades. Service life of a reinforced concrete structure is dependent on the corrosion process, specifically chloride threshold value. Chloride threshold value is a distinctive property and is dependent on several factors such as the supplementary cementitious material used, presence of surface cracks, water to binder ratio, type of steel reinforcement, exposure conditions, measurement methods, etc. Although chloride threshold value is an influential parameter in service-life prediction, a definitive chloride threshold value considering these factors is not reported in the existing literature and standards. Moreover, values adopted in many analytical tools for service life predictions based on the type of steel reinforcement alone are not appropriate and leads to inaccurate calculations. There is a gap in the available literature in understanding the selection of suitable chloride threshold values to be adopted for a specific system. Therefore, it is imperative to study the variation of chloride threshold value with exposure conditions as well as other influencing parameters, to achieve proper service life prediction. In the paper, several influencing parameters on chloride threshold value and its significance on prediction method are comprehensively reviewed. Moreover, suitable recommendations are highlighted for Indian and international standards at the later part of the study.

In this paper a hybrid cavity substrate integrated waveguide filter is proposed and demonstrated for Ku band application. Hybrid cavity which is the combination of both circular and rectangular cavity, showcases a better frequency selectivity and Quality Factor in comparison with other cavity based substrate integrated waveguide filters. Quality Factor requirements are met by the introduction of shorting posts at specified points inside the cavity. Filter operates at a frequency of 13GHz with an optimized Q factor of 377.096. The detailed analysis of the proposed structure is simulated and studied using the ANSYS HFSS software.

In this paper a Substrate Integrated Waveguide based filter is designed in Ku Band by making use of a Circular Cavity at the center. Furthermore, in order to enhance the Q factor of the filter shorting posts are provided at optimized positions within the Circular Cavity. The designed filter operates at a frequency of 16.93 GHz and is optimized for a Q factor of 367. The filter parameters are acquired using the ANSYS HFSS simulator.