Liquid mixture control system using PLC

The principle of the Liquids Mixture Control System By using PLC is to mix two or more types of liquids with different PH values, in order to acquire new PH value with correct composition, which to maintain product quality .These processes exist in beverage, drinkingwater, food, pharmaceuticals, chemistry, refinery indutries, also important for fish hatcheries, water conditioning and aquaculture, etc, moreover correct composition of PH value in our diet is important for our health,therefore for this project, volumetric of one type of liquid,can be determined its quantity of volume before entering into the Mixture tank and then, another liquid is entered automatically into this Mixture Tank,after that the mixing process will be done,which this system determined PH value automatically that macthing the PH value requirement as a complete product.Programmable Logic Controller (PLC) with analogue input signal is used to control this Liquids Mixture Control system.This system consist of six tanks, with one mixturer motor and also five pumps are used to control the system via PLC. PH sensor is used to detect PH value of the mixture, which this signal is fed to analogue input PLC teminal, that to be used for comparing PH value required as a product. The user can select volume one type of liquid to be entered into Mixture Tank, by pressing select buttons on the control panel board.This project can be used for manufacturing industries base on liquids and also for fish hatcheries, water conditioning and aquaculture ,which have been proved by project analyzing and testing results

Prototype-Design of Soil Movement Detector Using IoT Hands-on Application

The landslide disaster that killed people occurred due to public ignorance of the type of soil prone to landslides. Several efforts have been made to create prototype tools for soil movement detection. However, researchers using the Internet of Things (IoT) technology are still limited. The IoT allows for the transmission of data over an internet connection, is always connected, offers remote control capabilities, and data sharing. All of this served as the prototype design of foundation for the soil movement detection. A light-based proximity sensor is used in system, and its output is represented as a movement of the soil on an inclined plane. F furthermore, the data used as input for the NodeMCU ESP8266 microcontroller is linked to the internet. The output is an HMI in the form of an LCD monitor that displays the soil movement measurement. The simulation of disturbances in an inclined plane is done differently depending on the frequency and duration. Moreover, monitoring is carried out by transferring processed data to the Blynk platform, which is subsequently shown in real time via the Blynk Android application. The test results of the tool used three distinct samples, as well as varied disturbance frequencies and durations. With the soil samples, the biggest movement data was 5cm achieved at a disturbance frequency of 5Hz and 40 seconds duration. The largest movement data for sand samples was 11cm at a disturbance frequency of 3Hz and 50 seconds duration, followed by largest movement data for sand soil mixture samples was 8cm at a disturbance frequency of 5Hz and 50 seconds duration. People should not reside on slopes, especially if the soil's primary component is sand.Bencana longsor yang memakan korban jiwa tersebut terjadi karena ketidaktahuan masyarakat akan jenis tanah yang rawan longsor. Beberapa upaya telah dilakukan untuk membuat prototipe alat pendeteksi gerakan tanah. Namun, peneliti yang menggunakan teknologi Internet of Things (IoT) masih terbatas. IoT memungkinkan transmisi data melalui koneksi internet, selalu terhubung, menawarkan kemampuan kendali jarak jauh, dan berbagi data. Semua ini berfungsi sebagai prototipe desain pondasi untuk deteksi gerakan tanah. Sensor jarak berbasis cahaya digunakan dalam sistem, dan outputnya direpresentasikan sebagai pergerakan tanah pada bidang miring. Selanjutnya data yang digunakan sebagai input mikrokontroler NodeMCU ESP8266 terhubung dengan internet. Outputnya berupa HMI berupa monitor LCD yang menampilkan hasil pengukuran pergerakan tanah. Simulasi gangguan pada bidang miring dilakukan secara berbeda tergantung pada frekuensi dan durasi. Selain itu, pemantauan dilakukan dengan mentransfer data yang diproses ke platform Blynk, yang selanjutnya ditampilkan secara real time melalui aplikasi Blynk Android. Hasil pengujian alat menggunakan tiga sampel yang berbeda, serta frekuensi dan durasi gangguan yang bervariasi. Dengan sampel tanah, data pergerakan terbesar adalah 5cm yang dicapai pada frekuensi gangguan 5Hz dan durasi 40 detik. Data pergerakan terbesar untuk sampel pasir adalah 11cm pada frekuensi gangguan 3Hz dan durasi 50 detik, diikuti oleh data pergerakan terbesar untuk sampel campuran tanah pasir adalah 8cm pada frekuensi gangguan 5Hz dan durasi 50 detik. Orang tidak boleh tinggal di lereng, terutama jika komponen utama tanahnya adalah pasir

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

none5noNatural disasters cause enormous damage and losses every year, both economic and in terms of human lives. It is essential to develop systems to predict disasters and to generate and disseminate timely warnings. Recently, technologies such as the Internet of Things solutions have been integrated into alert systems to provide an effective method to gather environmental data and produce alerts. This work reviews the literature regarding Internet of Things solutions in the field of Early Warning for different natural disasters: floods, earthquakes, tsunamis, and landslides. The aim of the paper is to describe the adopted IoT architectures, define the constraints and the requirements of an Early Warning system, and systematically determine which are the most used solutions in the four use cases examined. This review also highlights the main gaps in literature and provides suggestions to satisfy the requirements for each use case based on the articles and solutions reviewed, particularly stressing the advantages of integrating a Fog/Edge layer in the developed IoT architectures.openEsposito M.; Palma L.; Belli A.; Sabbatini L.; Pierleoni P.Esposito, M.; Palma, L.; Belli, A.; Sabbatini, L.; Pierleoni, P

IoT based early warning system for torrential floods

S obzirom na to da je pretežno planinska zemlja, u Bosni i Hercegovini se povremeno dešavaju elementarne nepogode, pre svega poplave, koje mogu prouzrokovati značajnu materijalnu štetu i ljudske žrtve. Postojeći sistem za zaštitu od poplava je zasnovan na praćenju vodostaja velikih reka. Nasuprot tome, katastrofalne poplave su kratkotrajan i turbulentan fenomen, koji može izazvati lavine, ozbiljnu materijalnu štetu i gubitak ljudskih života. Sakupljanjem i analiziranjem podataka u karakterističnim tačkama terena je moguće otkriti situacije koje bi mogle da dovedu do poplave, nizvodno u rečnom basenu. Automatsko grupisanje takvih podataka od strane nadležnih službi bi moglo da obezbedi pravovremenu organizaciju odbrane od poplava. Integracijom softverskih komponenti, senzora i mikrokontrolera sa mrežnim serverom i namenskim softverom je stvoren sistem za rano upozoravanje, sposoban da na vreme uoči rizik od izlivanja reka, kao i rizik od katastrofalnih poplava i lavina. Sistem je zasnovan na mreži automatskih meteoroloških stanica (AMS). koje centralnom serveru šalju podatke u pravilnim vremenskim intervalima, da bi se ovi podaci nakon dalje obrade prikazali osoblju sa odgovarajućim pristupom sistemu.Being predominantly a mountainous country, in Bosnia and Herzegovina natural disasters periodically occur, especially floods, which can cause extensive material damage and human casualties. The existing flood defense system is focused on monitoring the situation on major rivers. In contrast, torrential floods are short-lived but turbulent phenomena, causing landslides, extensive material damage and loss of human lives. By collecting data from characteristic points on the terrain and analyzing them, it is possible to detect a situation which could cause torrential floods further in the river basin. Automated aggregation of such data by the competent services could provide timely organization of flood defenses. By integrating hardware components, sensors, microcontrollers with a Web server and custom built software, an early warning system was created capable of providing timely alerts to the risks of pouring of the rivers, as well as the emergence of torrential streams or landslides. The system is based on a network of automatic meteorological stations (AMS), which submit data at regular intervals to a central server, where this data is further processed and displayed to persons with appropriate authorization level to access the system

IoT based early warning system for torrential floods

S obzirom na to da je pretežno planinska zemlja, u Bosni i Hercegovini se povremeno dešavaju elementarne nepogode, pre svega poplave, koje mogu prouzrokovati značajnu materijalnu štetu i ljudske žrtve. Postojeći sistem za zaštitu od poplava je zasnovan na praćenju vodostaja velikih reka. Nasuprot tome, katastrofalne poplave su kratkotrajan i turbulentan fenomen, koji može izazvati lavine, ozbiljnu materijalnu štetu i gubitak ljudskih života. Sakupljanjem i analiziranjem podataka u karakterističnim tačkama terena je moguće otkriti situacije koje bi mogle da dovedu do poplave, nizvodno u rečnom basenu. Automatsko grupisanje takvih podataka od strane nadležnih službi bi moglo da obezbedi pravovremenu organizaciju odbrane od poplava. Integracijom softverskih komponenti, senzora i mikrokontrolera sa mrežnim serverom i namenskim softverom je stvoren sistem za rano upozoravanje, sposoban da na vreme uoči rizik od izlivanja reka, kao i rizik od katastrofalnih poplava i lavina. Sistem je zasnovan na mreži automatskih meteoroloških stanica (AMS). koje centralnom serveru šalju podatke u pravilnim vremenskim intervalima, da bi se ovi podaci nakon dalje obrade prikazali osoblju sa odgovarajućim pristupom sistemu.Being predominantly a mountainous country, in Bosnia and Herzegovina natural disasters periodically occur, especially floods, which can cause extensive material damage and human casualties. The existing flood defense system is focused on monitoring the situation on major rivers. In contrast, torrential floods are short-lived but turbulent phenomena, causing landslides, extensive material damage and loss of human lives. By collecting data from characteristic points on the terrain and analyzing them, it is possible to detect a situation which could cause torrential floods further in the river basin. Automated aggregation of such data by the competent services could provide timely organization of flood defenses. By integrating hardware components, sensors, microcontrollers with a Web server and custom built software, an early warning system was created capable of providing timely alerts to the risks of pouring of the rivers, as well as the emergence of torrential streams or landslides. The system is based on a network of automatic meteorological stations (AMS), which submit data at regular intervals to a central server, where this data is further processed and displayed to persons with appropriate authorization level to access the system

Advancements, Challenges, and Future Directions in Rainfall-Induced Landslide Prediction: A Comprehensive Review

Rainfall-induced landslides threaten lives and properties globally. To address this, researchers have developed various methods and models that forecast the likelihood and behavior of rainfall-induced landslides. These methodologies and models can be broadly classified into three categories: empirical, physical-based, and machine-learning approaches. However, these methods have limitations in terms of data availability, accuracy, and applicability. This paper reviews the current state-of-the-art of rainfall-induced landslide prediction methods, focusing on the methods, models, and challenges involved. The novelty of this study lies in its comprehensive analysis of existing prediction techniques and the identification of their limitations. By synthesizing a vast body of research, it highlights emerging trends and advancements, providing a holistic perspective on the subject matter. The analysis points out that future research opportunities lie in interdisciplinary collaborations, advanced data integration, remote sensing, climate change impact analysis, numerical modeling, real-time monitoring, and machine learning improvements. In conclusion, the prediction of rainfall-induced landslides is a complex and multifaceted challenge, and no single approach is universally superior. Integrating different methods and leveraging emerging technologies offer the best way forward for improving accuracy and reliability in landslide prediction, ultimately enhancing our ability to manage and mitigate this geohazard

Dense and long-term monitoring of Earth surface processes with passive RFID -- a review

Billions of Radio-Frequency Identification (RFID) passive tags are produced yearly to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing to monitor earth surface processes. Indeed, passive tags can cost 10 to 100 times less than wireless sensors networks and require little maintenance, facilitating years-long monitoring with ten's to thousands of tags. This study reviews the existing and potential applications of RFID in geosciences. The most mature application today is the study of coarse sediment transport in rivers or coastal environments, using tags placed into pebbles. More recently, tag localization was used to monitor landslide displacement, with a centimetric accuracy. Sensing tags were used to detect a displacement threshold on unstable rocks, to monitor the soil moisture or temperature, and to monitor the snowpack temperature and snow water equivalent. RFID sensors, available today, could monitor other parameters, such as the vibration of structures, the tilt of unstable boulders, the strain of a material, or the salinity of water. Key challenges for using RFID monitoring more broadly in geosciences include the use of ground and aerial vehicles to collect data or localize tags, the increase in reading range and duration, the ability to use tags placed under ground, snow, water or vegetation, and the optimization of economical and environmental cost. As a pattern, passive RFID could fill a gap between wireless sensor networks and manual measurements, to collect data efficiently over large areas, during several years, at high spatial density and moderate cost.Comment: Invited paper for Earth Science Reviews. 50 pages without references. 31 figures. 8 table